About the Role:
We are looking for a highly skilled and innovative AI Engineer to join our growing technology team in Bangalore. The ideal candidate will have strong expertise in Generative AI, Agentic AI frameworks, RAG pipelines, LLM integrations, and modern full-stack development practices.
This role requires hands-on experience in building scalable AI-powered applications, integrating enterprise data systems, developing multi-agent orchestration workflows, and deploying production-grade AI solutions.
The candidate should be passionate about emerging AI technologies and capable of delivering robust, secure, and scalable intelligent systems.
Key Responsibilities:
- Develop scalable RESTful and streaming APIs using FastAPI or Flask with clean architecture and API documentation.
- Build responsive and reusable frontend components using React.js integrated with AI-powered backend services.
- Integrate Large Language Models (LLMs) such as OpenAI GPT-4o, Anthropic Claude, Gemini, and open-source models like Llama/Mistral with enterprise applications and data sources.
- Design, optimize, and iterate prompts including system prompts, few-shot examples, and chain-of-thought prompting techniques.
- Develop and maintain CI/CD pipelines using GitHub Actions, Jenkins, GitLab CI, or Azure DevOps.
- Utilize GitHub for version control, pull requests, and collaborative development workflows.
- Participate in Agile ceremonies using JIRA including sprint planning, story estimation, backlog grooming, and retrospectives.
- Research and adopt emerging AI tools, frameworks, and best practices while contributing to internal knowledge sharing initiatives.
- Design and develop Agentic AI systems using frameworks such as LangChain, LangGraph, CrewAI, or AutoGen.
- Build, optimize, and maintain Retrieval-Augmented Generation (RAG) pipelines using vector databases including Pinecone, Weaviate, Chroma, or pgvector.
- Implement multi-agent orchestration workflows involving memory management, tool calling, task delegation, and agent loops.
- Ensure scalability, reliability, security, and observability of AI systems deployed in production environments.
Required Skills:
Technical Skills:
- Strong proficiency in Python programming with focus on clean code practices, unit testing, and type hints.
- Hands-on experience with Agentic AI frameworks such as LangChain, CrewAI, AutoGen, or similar technologies.
- Deep understanding of RAG architecture including chunking strategies, embeddings, semantic search, retrieval optimization, and re-ranking.
- Experience working with vector databases and similarity search concepts.
- Strong understanding of LLMs, tokenization, context management, prompt engineering, and inference optimization.
- Frontend development experience using React.js including Hooks, functional components, Redux/Zustand state management.
- Expertise in FastAPI including async programming, dependency injection, and Pydantic models.
- Working knowledge of CI/CD tools such as GitHub Actions, Jenkins, Azure DevOps, or GitLab CI.
- Strong Git workflow practices including branching strategies, semantic commits, and code reviews.
- Experience working in Agile/Scrum development environments using JIRA.
Good to Have:
- Experience with cloud platforms including AWS (Bedrock, SageMaker), Azure OpenAI, or Google Vertex AI.
- Containerization and orchestration experience using Docker and Kubernetes.
- Knowledge of observability and tracing tools such as LangSmith, Arize Phoenix, Datadog, or OpenTelemetry.
- Understanding of AI safety, prompt injection prevention, and guardrail frameworks such as NeMo Guardrails or Guardrails AI.
- Exposure to fine-tuning, RLHF workflows, or custom model training.
- Familiarity with SQL/NoSQL databases and modern data pipeline architectures.
Why Join Us?:
- Opportunity to work on cutting-edge AI and Agentic AI technologies.
- Exposure to enterprise-scale AI product development.
- Collaborative and innovation-driven work culture.
- Career growth in one of the fastest-growing AI domains.
- Opportunity to build impactful AI solutions with modern tech stacks.
