Senior AI Engineer

Tata Consultancy Services Limited
Irvine, United States of America
2 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Senior
Compensation
$ 150K

Job location

Irvine, United States of America

Tech stack

Java
API
Artificial Intelligence
Amazon Web Services (AWS)
Continuous Integration
Data Architecture
Information Engineering
Data Governance
DevOps
Distributed Computing Environment
Distributed Systems
Amazon DynamoDB
Elasticsearch
Graph Database
Identity and Access Management
Python
Machine Learning
Modular Design
Node.js
Redis
Search Technologies
Software Engineering
Amazon Web Services (AWS)
Large Language Models
Multi-Agent Systems
Prompt Engineering
Spark
Spring-boot
Backend
Kubernetes
Infrastructure Automation Frameworks
Deployment Automation
Cloudwatch
Docker
Databricks
Microservices

Requirements

Do you have experience in Spark?, * 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, * 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

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