Description

• 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.

Requirements

• Ensure adherence to governance and 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

Job responsibilities

• 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

• Education: Bachelor's or Master's degree in Computer Science, Computer or Electrical Engineering, Mathematics, or a related field.