Join us to shape tomorrow

About the Role

ROLE PROFILE: Hunter First → Consultative Seller Second → Presales Orchestrator Third

Infocusp is looking for a hands-on Manager / Senior Manager – Business Development & Presales to drive qualified pipeline creation and opportunity progression, primarily for the US market. This is a hunter-led role combining Business Development, Demand Generation, Inside Sales and Presales.

The individual will identify target accounts, initiate enterprise conversations, qualify opportunities, understand customer business and technology priorities, and work with Sales, Solutioning, Delivery, Capability and Marketing teams to shape differentiated propositions that progress toward commercial closure. A good understanding of AI, Data, Software Engineering and Digital/Product Engineering services is expected. Regular overlap with US business hours is required.Key Responsibilities

1. Business Development, Demand Generation & Account Intelligence

• Drive targeted outbound business development across identified US accounts, industries and buyer personas; research business priorities, technology initiatives, leadership changes and buying signals.
• Personally engage prospects through cold/warm calls, email, LinkedIn, social selling, referrals and campaign/event follow-ups; build account-specific outreach rather than relying only on generic campaigns.
• Generate qualified conversations with CIOs, CTOs, CDOs, Engineering, Data/AI, Product, Digital and relevant business leaders; partner with Marketing on targeted and account-based initiatives.
• Track and improve funnel progression: Target Account → Engagement → Meeting → MQL → SQL → Qualified Opportunity → Proposal → Deal.

2. Discovery & Opportunity Qualification

• Conduct first-level discovery to understand the business problem, desired outcomes, technology landscape, decision criteria, budget, timelines, procurement process and key stakeholders.
• Map decision-makers, influencers, champions, technical evaluators and procurement stakeholders; apply BANT, MEDDICC or an internal qualification framework where appropriate.
• Determine whether opportunities should be pursued, nurtured or disqualified and prepare clear opportunity briefs before engaging internal solution and delivery teams.

3. Presales & Solution Positioning

• Translate customer challenges into clear business and technology problem statements and work with Solution Architects, Delivery Leaders, Capability teams and SMEs to shape relevant propositions.
• Support positioning across AI / GenAI / Agentic AI, Machine Learning, Data Engineering & Analytics, Cloud & Platform Engineering, Software & Product Engineering, and Digital / Platform Modernization.
• Develop executive-level value propositions and presentations that connect technology to revenue impact, cost optimization, productivity, faster time-to-market and risk reduction; support workshops, demos and PoCs when required.

4. Proposals, RFX & Deal Management

• Coordinate proactive pitches, proposals, RFIs, RFPs and RFQs with Sales, Solutioning, Delivery, Engineering, Finance, Legal and Leadership teams.
• Ensure proposals address the customer problem, articulate a differentiated Infocusp proposition, communicate business value and reflect realistic delivery capability; support bid/no-bid, pricing coordination and submission governance.
• Maintain strong follow-through on active opportunities, capture win/loss insights and help progress qualified deals toward commercial discussion and closure.

5. Account Mining, CRM & Pipeline Governance

• Work with Sales and Delivery to identify whitespace, cross-sell and upsell opportunities, additional buying centres and expansion propositions within existing accounts.
• Maintain accurate CRM data for opportunity stage, deal value, stakeholders, next actions, expected closure and ageing; ensure every active opportunity has a clear owner and next step.
• Support weekly/monthly pipeline reviews, funnel analysis, forecasting and management reporting; identify stalled opportunities and improve pipeline hygiene and conversion discipline.

Key Success Measures

Demand & Meetings: Target accounts engaged; qualified meetings;response rates; speed-to-lead

Conversion MQL→SQL; SQL→Opportunity; Opportunity→Proposal; Proposal→Win

Pipeline: Qualified pipeline generated; new-logo opportunities; progression velocity; ageing

Presales / RFX: Discovery quality; proactive pitches; proposal quality; turnaround; RFXeffectiveness

Account Growth Cross-sell and upsell opportunities; expansion pipeline

Commercial / Governance Revenue or bookings influenced; CRM accuracy; next-action compliance; forecast quality

Requirements

Experience & Core Competencies

• 10+ years of relevant experience across Business Development, Inside Sales, Enterprise Sales, Demand Generation, Presales, Solution Consulting or Technology Services Sales.
• Proven ability to personally generate qualified enterprise opportunities through outbound prospecting and strong discovery / consultative selling skills.
• Strong preference for experience in IT Services, AI/ML, Data Engineering/Analytics, Software Engineering, Product Engineering or Cloud/Digital Engineering; US-market exposure strongly preferred.
• Experience engaging senior business and technology stakeholders and coordinating complex proposals, RFPs and presales activities.
• Strong written, verbal, presentation, and business-storytelling skills with sound understanding of IT-services commercial models.
• Experience with Zoho, Salesforce, HubSpot, Odoo or similar CRM platforms; familiarity with sales-intelligence, prospecting and sales-automation tools preferred.
• Bachelor’s degree required; MBA or relevant postgraduate qualification is an advantage.

Indicative Role Focus – Model A

• 60% - Business Development, Demand Generation & Inside Sales
• 20% - Presales & Solution Positioning
• 10% - Proposals, RFX & Deal Management
• 10% - Account Mining, CRM & Governance

Working Requirements

• Full-time, work-from-office role based in Ahmedabad or Pune, with primary focus on the US market.
• Regular overlap with US business hours and flexibility for customer discussions outside standard India working hours.
• Willingness to travel for customer meetings, industry events or business-development activities when required.

About the role:

We are seeking a highly skilled Senior Data Engineer with strong hands-on experience in Google Cloud Platform (GCP), cloud infrastructure, data ingestion, and Python. The ideal candidate will have a proven track record of designing and implementing scalable data platforms, organizing GCP environments to meet data sovereignty requirements, and building secure and reliable data ingestion and transfer solutions.

Key Responsibilities:

1. GCP Architecture & Infrastructure

• Design, develop, and maintain scalable GCP infrastructure for enterprise data workloads.
• Architect and organize GCP environments to support data sovereignty and data residency requirements.
• Design appropriate GCP projects, environments, networking, storage, IAM, and security configurations for data platforms.
• Establish scalable and reliable cloud infrastructure patterns for data processing and storage.

2. Data Ingestion & Pipeline Engineering

• Design and implement robust data ingestion pipelines for structured and unstructured data sources.
• Build production-grade ingestion frameworks to reliably process and move data into GCP or similar storage.
• Develop scalable and fault-tolerant data pipelines with appropriate validation, monitoring, and error handling.
• Optimize data ingestion workflows for performance, reliability, and cost.
• Ensure data pipelines maintain data quality, integrity, and traceability throughout the ingestion process.

3. Python Development & Automation

• Develop production-grade data engineering applications and automation using Python.
• Build reusable libraries, services, and utilities to support data ingestion and processing workflows.
• Automate infrastructure and data engineering processes to improve operational efficiency.
• Implement appropriate logging, monitoring, error handling, and testing for Python-based services and pipelines.

4. Collaboration & Ownership

• Work closely with Data Engineers, Software Engineers, Cloud/Infrastructure Engineers, Security teams, and business stakeholders.
• Take ownership of technical initiatives from architecture and design through production deployment and ongoing support.

Requirements

• 5+ years of experience in Data Engineering, Cloud Engineering, or a related field.
• Strong hands-on experience with Google Cloud Platform (GCP).
• Proven experience designing and implementing GCP architecture and infrastructure for data workloads.
• Good understanding of GCP services such as Google Cloud Storage (GCS), BigQuery, Pub/Sub, Dataflow, Cloud Run/GKE, VPC, IAM, and Cloud Monitoring.
• Experience with cloud networking, security, authentication, authorization, and access control.
• Experience with infrastructure automation and Infrastructure as Code (IaC), preferably Terraform.
• Strong understanding of data quality, monitoring, observability, and production operational best practices.
• Experience organizing GCP environments to meet data sovereignty and data residency requirements.
• Strong experience building data ingestion pipelines and data processing workflows.
• Hands-on experience designing and implementing secure data transfer and proxy solutions.
• Strong proficiency in Python and experience building production-grade applications and data pipelines.
• Excellent communication skills and ability to work independently with minimal supervision.

Work Location: Ahmedabad/Pune

Benefits

• Group Health Insurance
• Flexible working hours
• WFH Flexibility

About the Role:

The Senior LLM Engineer will lead the design, development, and deployment of complex, autonomous agentic AI solutions within production environments, working across multi-agent frameworks and orchestrating large language models. The position is or scalable applied AI, with a focus on delivering robust and fair agentic systems that deliver organizational value, autonomy, and operational efficiency.

Responsibilities:

• Architect, design, and deploy scalable agentic AI systems that coordinate LLMs, multi-agent collaboration, and external tool integrations through advanced tool calling.
• Develop, maintain, and optimize AI-driven pipelines utilizing frameworks such as LangGraph, ADK and LangChain, enhancing data inference and orchestration.
• Integrate agentic AI solutions into enterprise workflows, automating complex business functions (e.g., customer service, supply chain, decision support).
• Proactively address system evaluation, debug AI agent workflows, and ensure compliance with emerging regulatory and ethical guidelines.
• Promote security, transparency, fairness, and reliability across all deployed agentic systems.
• Mentor junior engineers, contribute to cross-functional teams, and champion the adoption of state-of-the-art LLM technologies and practices.

Requirements

• At least 1 year of experience with LangGraph (must have)
• 4+ years of overall experience working on industry projects
• Experience with LangChain, and other agentic orchestration frameworks.
• Deep proficiency in designing and deploying multi-agent frameworks and sophisticated tool-calling or API orchestration pipelines.
• Design and implement continuous monitoring systems for autonomous AI agents, ensuring performance, reliability, adherence to ethical guardrails, and optimal cost/latency in production.
• Develop and execute scalable LLM evaluation methodologies (including code-based, LLM-as-a-Judge) to rigorously assess model quality, safety, and goal alignment.
• Proficiency in Python
• Familiarity with retrieval-augmented generation (RAG) and modern vector databases (Pinecone, Weaviate).
• Experience with cloud platforms (AWS, GCP, Azure), MLOps practices, and production-grade deployment.
• Strong understanding of data privacy, model security, and compliance with current AI regulations and frameworks.

Preferred Skills

• Experience with Hugging Face, Neo4j, or knowledge graphs.
• Background in autonomous decision-making systems, anomaly detection, and dynamic process optimization.
• Track record of publishing, presenting, or open-sourcing agentic AI innovations.
• Strong problem-solving aptitude, collaborative mindset, and excellent communication skills.

About the Role:

The individual will lead the design, development, and deployment of complex, autonomous agentic AI solutions within production environments, working across multi-agent frameworks and orchestrating large language models. The position is for scalable applied AI, with a focus on delivering robust and fair agentic systems that deliver organizational value, autonomy, and operational efficiency.

Responsibilities:

• Architect and deploy scalable multi-agent AI systems with advanced tool integration.
• Build and optimize AI pipelines using frameworks like LangGraph, ADK, and LangChain.
• Integrate agentic AI into enterprise workflows to automate complex business processes.
• Review and execute code written by AI agents to ensure correctness and maintainability.
• Review agent configurations, prompts, and tool wrappers to prevent behavioral or performance regressions.
• Audit agent-generated ML workflows to catch flaws like target leakage.
• Launch, monitor, and debug distributed training jobs and auto-repair loops.
• Design evaluation suites and end-to-end scenarios for non-deterministic agents.
• Debug agent workflows and align systems with regulatory and ethical standards.
• Ensure security, transparency, fairness, and reliability across AI systems.
• Mentor engineers and promote modern LLM practices across teams.

Requirements

• 4+ years of industry experience, including 1+ years with agentic orchestration frameworks (LangChain, LangGraph, ADK).
• Proficiency in multi-agent framework design, tool calling, API orchestration, and vector databases/RAG.
• Experience with continuous monitoring, telemetry, and observability tooling for non-deterministic AI agents.
• Strong background in LLM evaluation methodologies (code-based, LLM-as-a-Judge) and end-to-end testing.
• Strong Python skills (type hints, absl, absltest) and senior-level code/prompt reviewing capabilities.
• Practical knowledge of the ML lifecycle (data preprocessing, feature engineering, model design, JAX/TensorFlow).
• Experience launching and debugging distributed training jobs across cloud platforms (AWS, GCP, Azure).
• Knowledge of MLOps practices, data privacy, model security, and AI compliance regulations.

Preferred Skills:

• On-device ML (TFLite, Edge TPU, Gemini Nano, latency and power profiling).
• Experience with Hugging Face, Neo4j, or knowledge graphs.
• Background in autonomous decision-making systems, anomaly detection, and dynamic process optimization.
• Track record of publishing, presenting, or open-sourcing agentic AI innovations.
• Strong problem-solving aptitude, collaborative mindset, and excellent communication skills.

Location: Ahmedabad/Pune

About the Role

We are hiring a Senior Backend Engineer (Python / AWS) to build a production automated order placement system for an AI-driven systematic trading client.

The system turns trading signals into broker orders, tracks every order through its lifecycle and feeds fill results back to the client's portfolio optimizer. It must run reliably and safely, with a full audit trail.

Responsibilities

1. Order management and trading logic

• Design and build the order management layer: an explicit order state machine (new, sent, partially filled, filled, cancelled, rejected, expired).
• Make order submission idempotent, so retries and reconnects never create duplicate orders.
• Build a pluggable broker adapter for submit, cancel, replace, status and fill events over REST, WebSocket or FIX APIs.
• Implement pre-trade risk checks: position and notional limits, per-order size limits, restricted lists, price sanity checks and a manual plus automatic kill switch.
• Aggregate fills into positions and residual quantities, and pass a clean state snapshot to the optimizer each cycle.
• Implement configurable policies for unfilled orders: cancel, re-price or carry over.

2. Reliability, reconciliation and audit

• Build intraday and end-of-day reconciliation of orders, fills and positions against broker records, with break reports and alerts.
• Maintain an immutable, event-sourced audit trail of every signal, order, broker message and fill.
• Handle broker rate limits, outages and undocumented behaviour with retries, backoff and stale-order detection.
• Test partial fills, rejects and disconnects end to end in paper trading before any live order is placed.

3. Backend engineering on AWS

• Build asynchronous Python services integrated with the client's existing codebase.
• Use Redis for fast order and position state, caching, locks and messaging.
• Deploy on AWS (ECS, Lambda or EKS) with the platform engineer, using Terraform, CI/CD and separate dev, paper and prod environments.
• Add metrics, tracing and structured logs, with dashboards and alerts for latency, errors and stuck orders.

4. Ownership and collaboration

• Take part in discovery and the architecture proposal, and raise concerns about design or requirements early.
• Write runbooks and architecture docs.
• Review code and share best practices with the team.

Requirements

• 5–7+ years of experience in backend development, with production systems you have owned end to end.
• B.E. / B.Tech / B.S. in Computer Science or a related field. Candidates without these degrees but with strong experience in the areas below will be considered.
• Strong Python skills, including asyncio, typing, testing and a modern framework such as FastAPI.
• Hands-on production experience with Redis: data structures, pub/sub or streams, distributed locks and persistence trade-offs.
• Strong AWS experience (ECS/EKS, Lambda, SQS/SNS, RDS, IAM, Secrets Manager, CloudWatch) and Infrastructure as Code (Terraform, CloudFormation or equivalent).
• Solid work with PostgreSQL or another relational database, including transactions, consistency and schema design for financial records.
• Proven design of distributed, event-driven systems: idempotency, exactly-once or at-least-once processing, retries, failure handling and state machines.
• Finance knowledge is a must: positions, P&L, notional exposure, portfolio rebalancing, and how trades are booked and settled.
• Trading knowledge is a must: order lifecycle, order types (market, limit, stop), partial fills, slippage, pre-trade risk controls and broker reconciliation.
• Hands-on experience integrating with at least one broker or exchange API.
• Experience with Docker, CI/CD pipelines and observability tools (Prometheus/Grafana, Datadog or CloudWatch).
• An ownership mindset: you drive work to production, raise risks early and write clear documentation.
• Experience mentoring engineers and running code reviews.
• Clear written and spoken English, for working directly with the client's engineering leadership.

Nice to have

• Prior work at a hedge fund, prop trading firm, brokerage, fintech or quant platform.
• Built an order management system (OMS) or execution management system (EMS) that went live.
• Exposure to systematic or quantitative trading: signals, portfolio optimizers, backtesting and paper trading.
• Execution-quality work: order slicing (TWAP/VWAP), slippage and transaction-cost analytics.
• Apache Kafka or Kinesis for event streaming.
• Awareness of audit, compliance and data-retention needs in regulated trading.

About the Role

We are looking for a highly skilled Senior Backend Engineer  to design, develop, and scale robust backend platforms and applications. This role requires strong Python proficiency, excellent code comprehension skills, and the ability to identify subtle logical flaws, shortcuts, inaccuracies, and quality issues in AI-assisted software development workflows.

Responsibilities

1. Backend Engineering & Platform Development

• Design, develop, and maintain scalable backend services using Python, FastAPI, and asynchronous microservices architectures.
• Build and optimize data-intensive applications using PostgreSQL, Redis, MongoDB or equivalent technologies at production scale.
• Develop high-performance APIs and distributed systems to support AI-driven applications.

2. Code Review & Evaluation

• Review and analyze AI-generated code for correctness, maintainability, efficiency, and security.
• Evaluate code quality, logic, and implementation choices across various Python-based projects.
• Identify shortcuts, hallucinations, hidden assumptions, and incomplete implementations generated by AI systems.
• Validate whether generated code meets functional and technical requirements.

3. Benchmark Validation

• Review and validate agentic workflows and benchmark results.
• Verify the reliability and correctness of AI-generated evaluations and testing outcomes.
• Ensure benchmark methodologies accurately measure intended capabilities.

4. Technical Analysis

• Perform manual verification and root-cause analysis when automated or AI-assisted approaches fail.
• Investigate complex code behaviors and implementation decisions.
• Improve Agent efficiency in identifying user intent and providing actionable responses.

Requirements

• 4+ years of experience in backend development.
• B.E.\B.Tech\B.S. Candidates' entries with significant prior experience in the fields above will be considered.
• Strong experience in Python development.
• Excellent code reading and code comprehension abilities.
• Ability to identify logical errors, edge cases, and implementation flaws.
• Strong analytical and problem-solving skills.
• Hands-on experience with asynchronous microservices architectures.
• Expertise in PostgreSQL, Mongodb,  Redis, and distributed backend systems.
• Strong understanding of CI/CD pipelines and DevOps best practices.

Good to have

• Android debugging tools (ADB)
• Web technologies (DOM, JavaScript, Browser APIs)
• Web security fundamentals
• Protocol Buffers (Protobuf)
• TypeScript

About the Role

We are looking for a Fullstack Engineer (backend heavy)  who designs, develops, and maintains computer software using creativity and technical skills and applies the principles of software engineering to help solve new and ongoing problems for an organization.

Responsibilities

• Design, develop, test, and deploy full-stack web applications.
• Build and maintain backend services and APIs using Python and/ or Node.js, with a focus on performance, security and maintainability.
• Develop responsive and user-friendly interfaces using React and/ or Angular.
• Design and optimize database schemas, queries, and data models.
• Review AI-generated code for correctness, security, edge cases, test coverage and maintainability, and give clear, actionable feedback.
• Collaborate with product, design, and other engineering teams to deliver reliable, high-performance solutions.
• Work with CI/CD pipelines, automated testing, and deployment workflows.
• Evaluate and prototype open-source tools or new technologies when required.
• Ensure adherence to secure coding practices and data protection standards.

Requirements

• B.E.\B.Tech\B.S. candidates with significant prior experience in the fields above will be considered.
• 3+ years of experience in full-stack development.
• Strong hands-on experience in backend development using Python.
• Experience in frontend development using Angular and/ or React.
• Experience working with relational databases such as PostgreSQL or MySQL, and/or NoSQL databases such as MongoDB or DynamoDB.
• Good to have experience with AWS/GCP.  
• Strong logical and analytical skills to debug and reason through complex full-stack systems, understanding how components function and interact end-to-end.
• Strong understanding of software design principles, data structures, and algorithms.
• Experience working with REST APIs and modern web application architectures.