Agentic AI Engineer

24 hours ago

Pune Maharashtra India, Maharashtra MatchPoint Full time

Agentic AI Engineer


Job location: Pune / Bengaluru (WFO - Hybrid mode)


Experience:Minimum 5 years


Stack: Python, cloudplatforms (any), CI/CD pipelines, agenticAI


Role summary

We are looking for a hands-onengineer who can design, build,and deploy agenticAI systems. You will own end-to-end work from prototype to production, own CI/CD and release flows, and collaborate with product and infra teams to ship reliable, secure solutions. Deep practical experience with agent frameworks and real deployments matters more than a single cloud vendor.


What you will do

  • Build and extendagentic AI systems(multi-step agents, tool use, memory,orchestration).
  • Prototype and productionize LLM-based solutions using retrievaland memory patterns.
  • Design and operate CI/CD pipelines for model code, infra, and microservices.
  • Deploy, monitor, and troubleshoot servicesin cloud environments.
  • Work with vector stores,embedding pipelines, and RAG-style retrievalwhere needed.
  • Write clean, testablePython and automation scripts.
  • Collaborate with ML engineers, SRE, and product to define requirements and SLAs.


Must-have

  • 5+ years of professional software engineering experience.
  • Strong Python skillsand experience shippingproduction code.
  • Hands-on experience with agentic AI or agent frameworks (examples: LangChain, AutoGen, custom agent implementations).
  • Practical experience managing CI/CD pipelines (CI servers, pipelines as code, automated testing, deployment automation).
  • Solid cloud experience - deploying and operating apps/services in at least one major cloud provider.
  • Good debugging, observability, and incident-handling experience.

Nice-to-have

  • Familiarity with vector databasesand embedding workflows (Pinecone, Weaviate, Milvus, FAISS).
  • Experience with containerorchestration (Kubernetes / ECS) and infra-as-code.
  • Familiarity with model monitoring, model versioning, or MLOps tooling.
  • Prior work on multi-agent orchestration or distributed task queues.

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