Lead Manager Agentic AI Engineer Claude Code & Codex

We are looking for an Lead or a Manager Agentic AI Engineer to design build and deploy production-grade AI agents capable of executing complex multi-step workflows through natural language interactions.

The role will focus on integrating LLMs agent orchestration frameworks MCP tools AI coding agents context and harness engineering APIs and enterprise systems to build intelligent assistants that can reason use tools execute actions and validate results.

The ideal candidate will have hands-on experience building agentic workflows beyond simple chatbots or proof-of-concepts (PoCs) along with strong software engineering skills and experience taking AI solutions into production.

Key Responsibilities:

Agentic AI Development & Orchestration - Design and develop LLM-powered autonomous and semi-autonomous agents capable of executing complex multi-step workflows. Build agent workflows using frameworks such as LangGraph LangChain Semantic Kernel AutoGen or similar technologies. Implement planning task decomposition tool selection execution observation retry and validation loops. Develop agents that can interact with enterprise applications APIs databases and developer tools through natural language.

Context and Harness Engineering: Design and implement context engineering strategies that provide agents with the right instructions task context application state tools and relevant information at the right time. Develop AI agent harnesses that manage agent state tool access permissions execution workflows guardrails retries and verification. Engineer repository and application context for AI coding agents such as Claude Code OpenAI Codex or similar platforms. Develop effective agent instructions project context coding guidelines workflows and automated verification mechanisms to improve agent reliability and developer productivity. Optimize context usage to reduce unnecessary token consumption latency and LLM costs.

MCP & Tool Integration: Design and develop Model Context Protocol (MCP) servers and tools that enable agents to interact with enterprise applications and services. Integrate agents with Git GitHub/GitLab Artifactory Slack databases APIs CI/CD platforms and other enterprise tools. Build secure tool-calling mechanisms with appropriate authentication authorization permissions and human approval workflows. Develop reusable tools that enable agents to perform actions rather than simply generate responses.

LLM & Generative AI Engineering: Integrate and orchestrate LLMs for reasoning planning content generation code generation and task execution. Work with commercial and open-source LLMs and select appropriate models based on quality latency cost and task complexity. Implement prompt engineering and advanced context management strategies. Apply techniques such as structured outputs function/tool calling model routing and model fallback strategies. Implement RAG where required including document retrieval embeddings vector databases reranking and grounding.

Agent Evaluation & Reliability: Design evaluation frameworks to measure agent task completion tool-call accuracy response quality hallucination reliability and business outcomes. Implement LLM-as-a-Judge and automated evaluation pipelines for agentic and GenAI applications. Build regression testing and validation workflows for agent behavior. Implement guardrails error handling retry mechanisms and human-in-the-loop controls for high-risk actions.

Production Engineering & Deployment: Develop production-grade AI services using Python and FastAPI or similar frameworks. Deploy and operate agentic applications in cloud and enterprise environments. Design scalable architectures that support concurrent users long-running agent workflows and complex tool execution. Implement caching model/inference optimization asynchronous processing parallel execution and cost optimization strategies. Integrate AI applications with CI/CD monitoring logging tracing and observability platforms.

Enterprise AI Solutions: Translate complex business and product requirements into agentic AI solutions with measurable business impact. Work closely with product managers software engineers data scientists architects and business stakeholders. Build solutions that move beyond prototypes into scalable secure production-ready enterprise applications.

Qualifications :

• 510 years of experience in Data Science or AI/ML or Software Engineer out of which atleast 2 years in Generative AI and Agentic AI with hands-on experience building production-grade AI applications and agentic systems.
• Strong development skills in Python and experience building APIs and AI services using FastAPI or similar frameworks along with experience in context engineering and AI agent harness engineering including agent instructions application/task context permissions guardrails retries validation automated verification and context optimization.
• Experience with AI coding agents such as Claude Code OpenAI Codex or similar platforms including repository context agent instructions automated testing coding workflows and verification.
• Hands-on experience with A2A MCP (Model Context Protocol) including developing or integrating MCP servers and connecting agents with enterprise tools APIs databases and SaaS platforms.
• Hands-on experience with LLMs agent orchestration and multi-step/multi-agent workflows using frameworks such as LangGraph LangChain Semantic Kernel AutoGen or equivalent technologies.
• Strong understanding of agent architecture tool/function calling planning task decomposition state/memory management dynamic tool invocation and workflow orchestration.
• Experience with RAG embeddings vector databases semantic search chunking reranking and grounding with knowledge of LLM-as-a-Judge and automated GenAI evaluation.
• Strong software engineering and cloud experience including Git CI/CD Docker databases/SQL AWS/Azure/GCP with familiarity with asynchronous programming parallel processing observability and distributed systems.
• Strong understanding of LLM performance and production optimization including hallucination mitigation context windows token usage latency caching cost optimization and monitoring.
• Demonstrated ability to build secure scalable production-ready AI solutions with measurable business impact beyond POCs.

Additional Information :

Thrive & Grow with Us:

Competitive Salary: Your skills and contributions are highly valued here. We ensure your compensation reflects the knowledge expertise and experience you bring to the table.

Dynamic Career Growth: Our vibrant environment provides opportunities to grow rapidly with the right tools mentorship and experiences to accelerate your career.

Idea Tanks: Innovation lives here. Our Idea Tanks provide a platform to pitch experiment and collaborate on ideas that can shape the future.

Growth Chats: Participate in casual Growth Chats where you can learn from experienced colleagues exchange ideas and develop your skills in a collaborative environment.

Snack Zone: Stay fueled and inspired with a variety of snacks available in our Snack Zone to keep your energy high and ideas flowing.

Recognition & Rewards: Great work deserves recognition. Our Hive-Fives shoutouts and reward programs provide opportunities to celebrate contributions and bring great ideas to life.

Fuel Your Growth Journey with Certifications: Were committed to continuous learning and professional development. Enhance your expertise through company-sponsored certifications in AI Data Science Cloud and Analytics technologies.

Remote Work :

Yes

Employment Type :

Full-time