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Generative AI Engineer (LLM Expert – AWS Focus)

Generative AI Engineer (LLM Expert – AWS Focus)

BigRioBengaluru, IN
6 days ago
Job description

Job Title : Generative AI Engineer (LLM Expert – AWS Focus)

Location : Remote

Employment Type : Ongoing Contract

About BigRio

BigRio is a Boston-based, remote-first technology consulting firm specializing in advanced data, cloud, and software engineering solutions . We partner with forward-thinking organizations to deliver scalable, secure, and high-performance technologies , with deep expertise in AI / ML, data engineering, and AWS-native architectures .

Our clients span healthcare, life sciences, government, and enterprise sectors , and we’re known for tackling complex, high-impact challenges with cutting-edge innovation and measurable results .

About the Role

We’re seeking a hands-on Generative AI Engineer (LLM Expert) who combines strong AWS development experience (60%) with deep expertise in applied LLM engineering (40%) .

This role is ideal for an engineer who has built real-world applications using OpenAI APIs and retrieval-augmented generation (RAG) — not someone focused on traditional ML or model training. You’ll work with BigRio’s internal AI team and client partners to design, build, and optimize LLM-powered features , integrating them into cloud-native, production-ready systems.

This is a senior technical role , not a research or experimental position. The focus is on building, shipping, and scaling LLM applications using OpenAI models, LangChain, and AWS infrastructure .

Key Responsibilities

  • Design, develop, and deploy AWS-based applications (Lambda, API Gateway, ECS, RDS, S3, Secrets Manager) that integrate LLM-powered features.
  • Implement OpenAI-driven workflows , leveraging reasoning and non-reasoning models, temperature settings, and model versioning best practices.
  • Apply prompt engineering and prompt chaining techniques to improve LLM accuracy and performance for production workloads.
  • Build retrieval-augmented generation (RAG) pipelines using LangChain , ChromaDB , or similar frameworks.
  • Develop FastAPI or Flask-based backends that connect to OpenAI APIs and vector databases.
  • Build interactive front-ends and tools using Gradio or Streamlit for rapid prototyping and testing.
  • Ensure secure, containerized deployments using Docker and integrate SSO and role-based access controls .
  • Automate data pipelines and document workflows via Google Drive , AWS SDKs , or REST APIs .
  • Write production-grade Python code , following clean architecture, documentation, and CI / CD best practices.
  • Collaborate closely with AI engineers, DevOps teams, and clients to deliver enterprise-ready LLM applications .

Required Qualifications

  • 5+ years of experience in professional software development, with a strong focus on AWS cloud and backend systems .
  • 3+ years of direct experience working with OpenAI APIs, GPT models, and LLM application development .
  • Proven ability to build and deploy LLM-powered applications , not just experiment with models.
  • Knowledge of vector databases like Pinecone or FAISS is required.
  • Expertise in Python , FastAPI , and API-driven architecture.
  • Strong practical experience with LangChain , ChromaDB , RAG , and prompt engineering .
  • Proficiency in Docker , AWS IAM , and secure deployment practices.
  • Excellent communication skills — ability to explain LLM behavior, tradeoffs, and reasoning clearly to both technical and non-technical teams.
  • Comfortable working independently in a fast-paced, client-facing environment across time zones.
  • Nice to Have

  • Experience with LangGraph or other LLM orchestration frameworks.
  • Familiarity with MLOps , CI / CD pipelines, and observability for LLM workloads.
  • Exposure to healthcare, biotech, or regulated data environments .
  • Demonstrated experience explaining and documenting AI system design and decision-making for non-AI stakeholders.
  • What This Role is Not

    To set clear expectations, this is not a role focused on :

  • Classical machine learning or model training (e.g., TensorFlow, PyTorch-based model design).
  • Research, experimentation, or theoretical AI.
  • Low-code or no-code chatbot builders.
  • This is a pure LLM engineering and AWS application development role — building scalable, production-quality AI systems using OpenAI and related frameworks.

    Equal Opportunity Statement :

    BigRio is an equal-opportunity employer committed to creating a diverse and inclusive workplace. We value and promote diversity and prohibit discrimination based on various factors outlined by federal, state, or local laws. All qualified applicants will receive equal consideration for employment.

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