Senior AI Engineer

Overview:

Must have Technical skills:

5+ years of experience in software engineering, data engineering, or AI/ML engineering Strong proficiency in Python for AI/data workflows and automation Hands-on experience building solutions in AWS cloud environments Experience with:

Databricks (or similar) and Apache Spark for distributed data processing OpenSearch / Elasticsearch (including vector search) Graph databases (Neptune or similar) DynamoDB and Redis/ElastiCache

Experience building backend services and APIs (e.g., Java/Spring Boot, Node.js) Production experience with Docker and Kubernetes Experience with CI/CD pipelines and deployment automation Strong understanding of distributed systems, data architecture, and scalable design Preferred Qualifications

Experience with LLM/GenAI architectures (RAG, embeddings, prompt engineering) Familiarity with LangGraph, AutoGen, CrewAI, or similar agent orchestration frameworks Experience with LangChain or LlamaIndex Experience implementing LLM evaluation and observability frameworks Familiarity with AI security practices and threat models (prompt injection, guardrails) Experience working in regulated environments with strong data governance and compliance requirements Tech Stack

AWS: Neptune, OpenSearch, DynamoDB, ElastiCache (Redis), IAM, CloudWatch Data: Databricks, Apache Spark AI: LLM integrations, embeddings, vector search, RAG pipelines Agentic/LLM Tooling: LangChain, LlamaIndex, LangGraph, AutoGen, CrewAI Backend: APIs, microservices (e.g., Spring Boot, Node.js) DevOps: Docker, Kubernetes, CI/CD, Infrastructure as Code

Skills:

Artificial Intelligence