Coforge is hiring experienced AI/ML professionals for a Senior Technical Lead position focused on GenAI and Agentic AI. The role is designed for candidates with 5β8 years of experience, including 5+ years of software development, strong Python expertise and 2β3+ years of AI/ML or GenAI experience. The position is available in Bangalore and Hyderabad with 5 days of work from office.
This is particularly relevant for engineers who have progressed from Python/software development into production ML systems, LLM applications, RAG pipelines and AI agents.
π Job Details
- π’ Company: Coforge
- πΌ Designation: Senior Technical Lead
- π― Experience: 5β8 Years
- π Locations: Bangalore / Hyderabad
- π’ Work Model: 5 Days WFO
- π Python: 5+ Years
- π€ AI/ML/GenAI: 2β3+ Years
- π§ Core: Machine Learning, LLMs, GenAI, Agentic AI, RAG
- β‘ Additional: PySpark, API Integration, Java
- βοΈ Preferred Cloud: AWS
- π© Apply: shweta.1.verma@coforge.com
- π Include: Current CTC, Expected CTC, Notice Period & Current Location
π’ About Coforge
Coforge is a global digital services and solutions provider focused on helping enterprises transform through technology, data, cloud and AI. The company currently has more than 45,000 technology and business-process professionals across 33 countries and 54 global delivery centers.
Coforge has been placing significant emphasis on AI-native engineering, trusted AI, autonomous enterprises and industry-specific AI solutions. Its FY2024β25 annual report describes a Data & AI strategy covering data modernization and AI-focused accelerators, including responsible AI governance and enterprise GenAI capabilities.
This makes the position particularly relevant for professionals who want to work on enterprise-grade GenAI rather than only experimentation or proof-of-concept projects.
β Why This Role Is Good for Experienced Professionals
This is not a conventional Python developer position. The JD expects candidates to design, architect, test and launch production ML systems, including model deployment, evaluation, monitoring, data pipelines and fine-tuning workflows.
You would also work with RAG, vector retrieval, function calling and tool-using agents, which are becoming important components of enterprise AI applications. The role offers an opportunity to combine software engineering discipline with AI architecture and production deployment.
For candidates with 5β8 years of experience, the Technical Lead designation also provides scope to demonstrate technical ownership, architecture decisions, mentoring and measurable business impact.
π οΈ Skills Required
Candidates should have strong hands-on expertise in:
- π Python: Large-scale application development, OOP, asynchronous programming, APIs, testing and production debugging.
- π€ Machine Learning: Model development, evaluation, feature engineering, deployment and monitoring.
- π§ LLMs: API integration, prompt engineering, model selection, fine-tuning/adaptation and evaluation.
- π RAG: Embeddings, chunking, vector databases, retrieval strategies, reranking and grounding.
- π€ Agentic AI: Tool calling, function calling, agent orchestration, memory, guardrails and secure tool execution.
- βοΈ AWS: ECS/EKS, Lambda, S3, DynamoDB, Redshift, Step Functions and SageMaker.
- π³ Cloud Engineering: Containers, deployment, observability and infrastructure-as-code.
- β‘ PySpark: Distributed processing and large-scale data transformation.
- π API Integration: REST APIs, authentication, error handling and enterprise-system integration.
Knowledge of OpenAI, Gemini, Claude, Llama and Qwen is useful because the JD specifically expects familiarity with both commercial and open-source LLM ecosystems.
π― Expected Coforge Interview Rounds
A realistic process could therefore include:
- Round 1 β Technical Screening: Python, ML fundamentals, LLM concepts and project experience.
- Round 2 β Deep Technical: RAG architecture, agents, model evaluation, production ML and system design.
- Round 3 β Architecture/Client Technical: Enterprise integration, scalability, security, cloud and AI architecture.
- Round 4 β Techno-Managerial: Leadership, ownership, mentoring, stakeholder communication and business impact.
- Round 5 β HR/Final: Compensation, notice period, location and joining formalities.
The number of rounds can vary significantly depending on the client project.
π° Expected Salary Range
The job announcement does not disclose an official compensation band. Third-party salary data reports Coforge Technical Lead compensation broadly around βΉ13.5β43 LPA for 7β14 years, while reported individual Technical Lead salaries can vary substantially by experience and specialization.
For a 5β8 year Senior Technical Lead specializing in GenAI/Agentic AI, a reasonable market expectation could be approximately βΉ18β35+ LPA, depending on current CTC, GenAI depth, cloud expertise, leadership scope and client requirements. This is a market estimate, not an official Coforge salary range.
π Preparation Tips
π§ Design a complete RAG system: Be ready to explain document ingestion, chunking, embeddings, vector search, retrieval, reranking, prompt construction and response evaluation.
π€ Prepare an Agentic AI architecture: Explain how an agent decides when to call a tool, how permissions are controlled and how failures or hallucinations are handled.
π Focus on enterprise security: Prepare prompt injection, data leakage, PII protection, authentication, authorization, secure tool execution and audit logging.
π Know LLM evaluation: Be prepared to discuss hallucination rate, groundedness, relevance, latency, cost and offline/online evaluation.
βοΈ Revise AWS: Understand how you would deploy containerized AI services using ECS/EKS and when Lambda, S3, DynamoDB or SageMaker would be appropriate.
π Strengthen Python: Practice API development, concurrency, testing, error handling and production-quality code.
π‘ Prepare one end-to-end project: Be able to explain an AI solution from business requirement β architecture β model/LLM selection β RAG/agents β deployment β monitoring β measurable outcome.
π Resume Tips
Your resume headline should immediately communicate: Senior Technical Lead | GenAI | Agentic AI | LLM | RAG | Python | ML | AWS.
Do not simply list βChatGPT/OpenAIβ under skills. Demonstrate what you built and deployed. For example: βArchitected a production RAG platform using Python, vector retrieval and LLM APIs, improving knowledge-search accuracy while implementing evaluation and guardrail mechanisms.β
Highlight production deployment, model evaluation, monitoring, API integration, cloud architecture, security and business outcomes. If you have experience with multiple LLMs, explicitly mention them.
For senior profiles, include examples of technical leadership, mentoring, architecture reviews and cross-functional collaboration.
π How to Apply
π Application Link: Click Here
Interested candidates should email their updated resume to:
π© shweta.1.verma@coforge.com
Include these details in the application:
- Current CTC
- Expected CTC
- Notice Period
- Current Location
- Total Experience
- Relevant GenAI/AI-ML Experience
- Preferred Location: Bangalore/Hyderabad
