Senior AI Engineer

We are looking for an experienced AI Engineer to design and deliver scalable Gen AI solutions. The role involves building production-ready AI products using Python, React, and AWS, while leveraging modern architectures such as LLM pipelines, RAG, and agent-based systems. This role is for subcontractors.

Responsibilities

AI Engineer Responsibilities

Lead and actively contribute to the development of AI products, pilots and solutions, with a focus on clean, maintainable code using Python, React, and AWS tools.

Design, architect and build scalable Gen AI solutions, including LLM pipelines, Agentic, MCP, Graph/RAG architectures, and prompt-based applications and emerging tech.

Implement cloud-native solutions using AWS services such as EKS, Lambda, Fargate, Glue, and Athena.

Optimize performance of AI products, Drive continuous learning and experimentation with cutting-edge Gen AI methods, frameworks, APIs, and toolchains.

Work closely with product managers, data scientists, and domain experts to define technical solutions aligned with business needs.

Act as a subject matter expert (SME) on Gen AI technologies and help shape the organization’s AI roadmap.

Own end-to-end delivery of Gen AI solutions. Manage timelines, deliverables, and project milestones using Agile practices (Scrum/Kanban).

Monitor operational metrics and incident data to drive continuous improvement and reliability.

Ensure adherence to governance, DevSecOps protocols.

6+ years of progressive experience in engineering roles, including at least 1-2 years leading emerging tech or AI initiatives.

Gen AI models (GPT, Claude, Gemini, LLaMA) and prompt engineering techniques

Agentic AI, MCP, and Graph/RAG architectures

Gen AI Framework (LangChain, LlamaIndex, Amazon Bedrock)

Web application development using Next.js, React, TypeScript/JavaScript

AWS cloud services (EC2, ELB/GLB/NLB, EKS, Fargate, Lambda, Athena, Glue, Lake Formation)

Infrastructure as Code (Puppet, Terraform, Docker) and containerized deployments

ETL orchestration using Apache Airflow/DAGs

Vector/Graph databases (Weaviate, Milvus, PGVector, Neo4J, Neptune) and query optimization

Python programming (NumPy, Pandas, Matplotlib, Boto3)

Automated testing frameworks (Ragas, Playwright, Zephyr, Selenium,)

Familiarity with SDLC best practices, DevSecOps, Agile Scrum/Kanban, and work management tools (JIRA, Confluence, JIRA Align).

Knowledge of LLM fine tuning techniques

Experience in BI tools like QuickSight, Tableau

Knowledge of financial markets and enterprise data systems