Custom Software Engineer
Project Role Description : Develop custom software solutions to design, code, and enhance components across systems or applications. Use modern frameworks and agile practices to deliver scalable, high-performing solutions tailored to specific business needs.
Must have skills : AI Agents & Workflow Integration
Good to have skills : Google CES Conversational Agent
Minimum 5 year(s) of experience is required
Educational Qualification : 15 years full time education
Summary:
We're looking for an Agentic AI Engineer to design, build, and deploy autonomous and semi-autonomous AI agents that can reason, plan, and execute multi-step tasks using tools, APIs, and external systems. You'll work at the cutting edge of applied AI, building agentic workflows using frameworks like Google's Agent Development Kit (ADK), LangChain/LangGraph, CrewAI, AutoGen, or similar, integrating them with LLMs (Gemini, Claude, GPT, open-source models) to solve real business problems.
What You'll Do
Design and build agentic systems that can plan, reason, call tools, and orchestrate multi-step workflows with minimal human intervention
Develop and deploy agents using frameworks such as Google ADK, LangChain/LangGraph, Semantic Kernel, CrewAI, AutoGen, or comparable agent orchestration toolkits
Implement tool-calling, function-calling, and Model Context Protocol (MCP) integrations to connect agents with internal APIs, databases, and third-party services
Architect memory, state management, and context-handling strategies for long-running or multi-turn agent interactions
Build retrieval-augmented generation (RAG) pipelines and integrate vector databases (Pinecone, Weaviate, FAISS, Chroma, etc.) where needed
Evaluate, fine-tune, and select appropriate foundation models for specific agentic use cases, balancing cost, latency, and accuracy
Implement guardrails, evaluation frameworks, and observability (tracing, logging, eval harnesses) to ensure agent reliability, safety, and correctness
Collaborate with product, design, and domain experts to translate business workflows into agent capabilities and task decompositions
Write production-grade Python (and/or TypeScript) code, with strong testing, CI/CD, and deployment practices for agent services
Stay current with the rapidly evolving agentic AI ecosystem and proactively bring in new techniques, frameworks, and best practices
Document agent architectures, prompt strategies, and decision logic for maintainability and team knowledge-sharing
Required Qualifications
3+ years of software engineering experience, with at least 1+ years working directly with LLMs or generative AI systems in production
Hands-on experience with at least one agent framework (Google ADK, LangChain/LangGraph, CrewAI, AutoGen, Semantic Kernel, or similar)
Strong Python skills (production-quality code, not just notebooks) experience with async programming a plus
Practical understanding of prompt engineering, tool/function calling, and multi-agent orchestration patterns
Experience integrating LLM APIs (OpenAI, Anthropic, Google Gemini, etc.) and working within their rate limits, token economics, and context constraints
Familiarity with vector databases and RAG architecture
Understanding of evaluation methodologies for non-deterministic AI systems (offline evals, human-in-the-loop review, A/B testing)
Experience deploying services on cloud platforms (GCP, AWS, or Azure) using containers (Docker/Kubernetes)
Solid grasp of API design, microservices, and event-driven architectures
Nice to Have
Experience with Model Context Protocol (MCP) server/client implementations
Familiarity with Google Cloud's Vertex AI Agent Builder or similar managed agent platforms
Background in workflow orchestration tools (Airflow, Temporal, n8n)
Experience with observability/tracing tools for LLM apps (LangSmith, Arize, Langfuse, Weights & Biases)
Bengaluru
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