Senior AI Engineer
Role details
Job location
Tech stack
Requirements
Do you have experience in Spark?, * 5+ years of experience in software engineering, data engineering, or AI/ML engineering
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Strong proficiency in Python for AI/data workflows and automation
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Hands-on experience building solutions in AWS cloud environments
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Experience with:
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Databricks (or similar) and Apache Spark for distributed data processing
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OpenSearch / Elasticsearch (including vector search)
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Graph databases (Neptune or similar)
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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, * 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