WE’RE HIRING | AD / SENIOR MANAGER – AI AGENT ENGINEERING

Location: Bangalore, India | Hybrid

Experience: 10–12 Years

Role: Senior Engineering Leadership

Copperpod AI is looking for a hands-on AI Engineering Leader to lead and scale our AI Agent platform.

This is a role for someone who can architect, build, lead, and ship, someone who is comfortable diving into code, shaping technical direction, mentoring teams, and working directly with business and enterprise stakeholders.

What You’ll Own

- Lead and scale a team of Python/AI engineers building production-grade agentic workflows.
- Own the journey from problem definition to PoC, production, and scale.
- Architect scalable agentic systems using Python, FastAPI, AsyncIO, and event-driven architectures.
- Drive implementation of agent orchestration frameworks such as LangGraph, CrewAI, and AutoGen.
- Own RAG at scale, including vector DB strategy, retrieval quality, reranking, and evaluations.
- Build reliable agent tool-use across APIs, databases, RPA bots, and internal services.
- Bring deep expertise in Model Context Protocol (MCP) and context management across agents.
- Define production platforms using Docker, Kubernetes, CI/CD, and IaC.
- Establish observability, logging, tracing, evaluation, guardrails, safety, and cost governance for AI agents.
- Partner with MLOps and AWS teams on model lifecycle, deployment, and enterprise integrations.
- Work closely with Product, Business, and Executive stakeholders to translate complex business problems into scalable AI solutions.

What We’re Looking For

Experience

- 10–12 years of total experience.
- 6+ years in Python backend / AI / ML engineering.
- 4+ years leading engineering teams and delivering production AI/ML systems.
- Proven experience shipping 2+ agent-based products that reason, use tools,



and automate business or operations workflows.

Must-Have Technical Skills

- Expert Python: FastAPI, AsyncIO, Pydantic, distributed systems design.
- Agentic AI: LangChain, LangGraph, CrewAI, AutoGen, agent planning, memory, tool-use, and evaluations.
- RAG and Vector DBs: Architecture, tuning, retrieval, and reranking; experience with OpenSearch / ElasticCloud.
- Cloud and DevOps: Docker, CI/CD, AWS, AWS Bedrock / Bedrock Knowledge Bases.
- System Design: Async, event-driven, distributed agent workflows with strong observability.

Good to Have

- AWS AI Services - Bedrock, Bedrock KB, Textract, Transcribe, Lex, Connect, Polly.
- MLOps - model monitoring, A/B testing, and LLM cost optimization.
- LLM evaluation frameworks - Ragas, DeepEval, Phoenix.

The Leadership Mindset We Value

Technical Depth - You can get into the code, debug agent failures, and challenge architecture decisions.

Ownership - You take problems end-to-end and make things happen.

Communication - You can translate complex AI concepts into transparent business outcomes.

Innovation - You stay close to the rapidly evolving agentic AI landscape and bring relevant ideas into production.

About Copperpod AI

Copperpod AI is a global AI partner to enterprises, headquartered in New Jersey with a deep engineering base in India. We solve complex business problems through outcome-focused AI solutions across decision intelligence, operations, and customer experience.

Through our AI Lab, agile delivery pods, and AI Foundry, we work with enterprises to move from ideas and prototypes to real-world AI deployments across fashion, retail, manufacturing, and healthcare.

Interested in joining us?

Send your resume to [email protected] or [email protected] or [email protected]

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📌 Senior Manager - AI agent engineering (Bengaluru)
🏢 Copperpod AI
📍 Bengaluru