AI/ML Engineer

IntraEdge
India

Job Title: AI/ML Engineer

Location: Pune/Remote

Job Type: Full time

Shift timing: 2pm to 11pm IST

Need minimum 6 - 7 years of experience.

Key Responsibilities

  • Design, develop, and maintain AI-powered applications and platform services.
  • Build and enhance Generative AI solutions using enterprise-approved LLMs and AI frameworks.
  • Develop scalable REST APIs, microservices, and backend services supporting AI workloads.
  • Integrate AI services with enterprise platforms, governance controls, observability, and security frameworks.
  • Collaborate with Product, Engineering, Architecture, UX, Security, and Data teams to deliver production-grade AI capabilities.
  • Implement model evaluation, prompt engineering, experimentation, and AI quality measurement frameworks.
  • Contribute to AI Platform products including evaluation services, AI agents, AI governance integrations, model routing, and data protection services.
  • Participate in cloud deployment, operational support, performance optimization, and troubleshooting activities.
  • Support CI/CD automation and infrastructure-as-code initiatives.
  • Ensure solutions meet enterprise requirements for scalability, security, reliability, compliance, and observability.

Must-Have Skills

  • 6+years of Software engineering experience.
  • 2+ years of hands on Generative AI or LLM application development experience.
  • Strong proficiency in Python.
  • Experience building APIs and microservices in cloud environments.
  • Hands-on experience with LangChain, RAG, vector search, and prompt engineering.
  • Experience deploying applications to Kubernetes.
  • Strong understanding of software design patterns and scalable architecture.
  • Experience with SQL and NoSQL databases.
  • Familiarity with Git-based development workflows and CI/CD pipelines.
  • Strong problem-solving and communication skills.
  • Ability to work in Agile/Scrum environments.

Tech Stack:

Python, Large Language Models (OpenAI, Anthropic, Gemini, Llama) , Retrieval-Augmented Generation (RAG), Prompt Engineering, AI Agents / Agentic Workflows , Model Evaluation Frameworks ,Embeddings and Semantic Search, Google Cloud Platform (GCP) , Vertex AI , Kubernetes (GKE preferred) , Docker , Cloud Storage , API Gateway technologies, FastAPI, Microservices Architecture , Event-Driven Architecture, Kafka, MongoDB, GitHub, GitHub Actions, CI/CD Pipelines, OpenTelemetry

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