Sr. Tech Lead - Application Development N 4D

Sr. Tech Lead - Application Development N Ready to turn bold ideas into real-world impact? At Genpact, we don’t just adapt to change, we lead it. AI and digital innovation are transforming the way businesses work, and we’re at the forefront of it. Genpact’s AI Gigafactory , our industry-first accelerator, exemplifies how we scale advanced technology solutions to help global enterprises work smarter, grow faster, and transform at scale. Whether tackling complex challenges through large-scale models or agentic AI , our breakthrough solutions tackle companies’ most complex challenges. If you thrive in a fast-moving, innovation-driven environment, love building and deploying cutting-edge AI solutions, and want to push the boundaries of what’s possible, this is your moment. Genpact (NYSE: G) is an agentic and advanced technology solutions company. We leverage process intelligence and artificial intelligence to deliver measurable outcomes. With a strong partner ecosystem and decades of client trust, we provide innovative solutions that transform how businesses run. Powered by a team with an active learning mindset and client centricity at its core, we deliver lasting value for the world’s leading enterprises. Get to know us at genpact.com and on LinkedIn , YouTube , X , and Facebook . Job Description relevant years in Python-first software development; hands-on AI/agentic development experience required A hands-on Python developer who builds, tests, and maintains the agents, pipelines, and AI-enabled features of the IPS insurance broking platform. This is a coding role — candidates are expected to write production-quality Python every day, working within the Microsoft Agent Framework multi-agent pipeline running on Azure. 4D band targets developers who can own a feature end-to-end with light oversight; 4C band targets developers who can deliver well-defined tasks within the platform with close collaboration. Responsibilities Agentic AI Development (Primary Focus) Build and maintain agents within the Microsoft Agent Framework multi-agent pipeline — including workflow design in the visual designer, prompt engineering, tool/function registration, and agent-to-agent handoff logic. Write Python services (FastAPI) that form the backend of the agentic platform — including async patterns, Azure SDK for Python, and RESTful API design. Integrate Azure AI services into the platform: Azure OpenAI (LLM invocation, token budgeting, retry/fallback), Azure AI Foundry (model deployment, versioning), Azure AI Content Understanding (document extraction schemas, classifier configuration, confidence scoring), Azure AI Translator, and Azure AI Search (RAG, vector-search patterns). Implement rules engine logic for hard-check and soft-check validation rules covering insurance broking workflows — policy search, co-broker duplicate detection, mid-term binding, carrier-portal submission. Develop Human-in-the-Loop workflow components: exception queues, reviewer edit flows, escalation paths. Platform Engineering Write clean, version-controlled, well-tested Python code — unit tests, integration tests, and tolerance-based assertions for non-deterministic LLM outputs. Integrate with insurance broking systems via REST APIs: AIM API, ImageRight, carrier portals, and Cora Sequence — including authentication patterns (OAuth2, managed identities). Contribute to CI/CD pipelines for the platform (Azure DevOps or GitHub Actions); follow DevSecOps practices. Participate in code reviews, sprint planning, and retrospectives; maintain technical documentation. Debug and resolve production issues in the agentic pipeline; contribute to root-cause analysis. Minimum Qualifications Core Technologies — Must-Have (tested hands-on in interview) Strong, hands-on Python (PRIMARY language — non-negotiable): FastAPI, async/await, Pydantic, Azure SDK for Python, RESTful API development, clean code practices. Must be able to write production Python from scratch in the interview, not just describe it. Microsoft Agent Framework — hands-on development experience building agents, registering tools/functions, and designing multi-agent workflows. Candidates with Semantic Kernel experience are eligible; migration to Microsoft Agent Framework is in progress on the platform. Azure OpenAI — LLM API invocation, prompt construction, token budgeting, retry/fallback strategies, structured output parsing. Azure platform fundamentals: Azure Key Vault (secrets), managed identities / Microsoft Entra ID (RBAC), Azure Storage, Azure Monitor / Application Insights — sufficient to develop and deploy features on the platform independently. REST API integration: consuming external REST APIs with proper authentication (OAuth2, API keys, managed identities); JSON handling; OpenAPI/Swagger contract familiarity. Git — version control, branching, code review workflow; CI/CD basics (Azure DevOps or GitHub Actions). Unit and integration testing — pytest or equivalent; writing tests for deterministic and non-deterministic (LLM) outputs. Relevant years of experience; able to own a feature end-to-end from design through production deployment with light oversight from the Tech Architect. Azure AI Foundry — model deployment management, versioning, and guardrails configuration. Strong understanding of multi-agent pipeline design: agent orchestration, tool registration, context window management, and prompt chaining strategies. Able to contribute to low-level design documents and integration pattern decisions; leads code review for 4C developers. Preferred Qualifications / Skills Azure AI Content Understanding — hands-on experience building document extraction schemas, configuring classifiers, and interpreting confidence scores; strongly preferred for this role given the CRC/IPS document processing pipeline. Azure AI Search — RAG pipeline implementation, vector-search index design, hybrid retrieval strategies. Azure AI Translator — document translation integration within an agentic pipeline. Insurance broking domain awareness: policy search, AIM, carrier portals, co-broker duplicates, mid-term binding — domain exposure is a significant plus; not a hard requirement for developers (the BA role carries domain ownership). Java familiarity (Spring Boot) — sufficient to read and debug the Java platform layer when integration issues span services; not required for the AI/agentic coding work. Event-driven patterns: Azure Service Bus, Kafka, or RabbitMQ for async messaging between platform components. MLOps basics: model versioning, deployment pipelines, monitoring of AI model outputs in production. Docker; Kubernetes basics — sufficient to containerise a Python service and understand how it runs in the platform. Technical Skill Checklist (Screening Reference) PRIMARY — Must-Have (tested hands-on in interview): Python — FastAPI, async/await, Pydantic, Azure SDK for Python, RESTful API development Microsoft Agent Framework — agent development, tool/function registration, multi-agent workflow design Azure OpenAI — LLM invocation, prompt engineering, token budgeting, structured output parsing Azure Platform — Key Vault, managed identities / Entra ID, Azure Storage, Azure Monitor / App Insights REST API integration — OAuth2 / managed identity auth, JSON, OpenAPI/Swagger Testing — pytest; unit + integration tests; tolerance-based assertions for LLM outputs Git + CI/CD — Azure DevOps or GitHub Actions; clean branching and code review practices SECONDARY — Strong Plus: Azure AI Content Understanding — document extraction schemas, classifier config, confidence scoring (strongly preferred) Azure AI Foundry — model deployment, versioning, guardrails (required at 4D band) Azure AI Search — RAG pipeline, vector-search index design, hybrid retrieval Azure AI Translator — document translation in agentic workflows Insurance broking integrations — AIM API, ImageRight, carrier portals, Cora Sequence REST Azure Service Bus / Kafka — async messaging between platform components OPTIONAL — Nice-to-Have: Java / Spring Boot familiarity — to read and debug the platform layer Docker; Kubernetes basics MLOps — model versioning, deployment pipelines, production AI monitoring Qualifications Bachelors - Computer Engineering, Bachelors - Computer Science, Bachelors - Information Technology, Masters - Software Engineering Certifications BUILD -IT/JAVA - Genpact, Oracle Certified Professional - Oracle Required Skills Actimize, Actimize, Agile Methodology, Alpha, Business Analysis, Business Reporting, CALMS (WCG), Calypso (Software), Capital Markets, Change Management, Client Relations, Collaboration Tools, Design Thinking, Executive Presence, Fenergo Client Lifecycle Management Solution, Inclusion, InfoLease, IntelliMatch, Kondor+, LeasePak, LeaseWave (Odessa), LexisNexis, Loan IQ, Misys: Summit, Modernizing Operations {+ 6 more} Language English (Required) Language Proficiency - English (OVERALL - Advanced - C1) Additional Job Location - Job Type Regular Master Skill List - DNU Application Development N Remote Type - Hybrid Work Shift - Flex Time (India) Why join Genpact?

• Lead AI-powered transformation – Drive innovation and solve real-world business challenges that matter
• Make an impact – Help global enterprises solve business challenges that matter
• Accelerate your career – Gain hands-on experience, mentorship, and world-class learning opportunities to stay ahead
• Work with the best – Join 140,000+ bold thinkers and problem-solvers who push boundaries every day
• Thrive in a values-driven culture – Our courage, curiosity, and incisiveness - built on a foundation of integrity and inclusion - allow your ideas to fuel progress Come join the 140,000+ coders, tech shapers, and growth makers at Genpact and take your career in the only direction that matters: Up. Let’s build tomorrow together. Genpact is an Equal Opportunity Employer and considers applicants for all positions without regard to race, color, religion or belief, sex, age, national origin, citizenship status, marital status, military/veteran status, genetic information, sexual orientation, gender identity, physical or mental disability or any other characteristic protected by applicable laws. Genpact is committed to creating a dynamic work environment that values respect and integrity, customer focus, and innovation. Furthermore, please do note that Genpact does not charge fees to process job applications and applicants are not required to pay to participate in our hiring process in any other way. Examples of such scams include purchasing a 'starter kit,' paying to apply, or purchasing equipment or training.