Senior AI Engineer

Tata Consultancy Services Limited
Oakland, United States of America
7 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
$ 170K

Job location

Oakland, United States of America

Tech stack

API
Artificial Intelligence
Cloud Engineering
Encodings
Fault Tolerance
Python
Search Technologies
Unstructured Data
Large Language Models
Multi-Agent Systems
Prompt Engineering
Generative AI
AI Platforms
Information Technology
Machine Learning Operations

Job description

o Prompt injection prevention o Access control and role based execution o Output validation and policy enforcement

  • Support observability for:

o Agent behavior and execution flow o Confidence scoring and failure detection o Usage patterns and anomaly detection

  • Design AI systems that are auditable, explainable, and enterprise ready

Collaboration & Technical Leadership

  • Provide technical leadership across AI and GenAI initiatives

  • Review AI designs, orchestration flows, and implementation quality

  • Mentor junior AI engineers on agent design and best practices

  • Collaborate with architects, data scientists, and platform engineers

Requirements

Senior AI Engineer with deep, hands on expertise in Generative AI, multi agent orchestration, and LLM based systems to design, build, and scale secure, production grade AI platforms. The role requires strong engineering rigor, practical experience beyond PoCs, and the ability to operationalize agentic AI in complex enterprise environments. Roles & Responsibilities Core Skills & Responsibilities Generative AI & LLM Engineering

  • Strong hands on experience building LLM powered applications for reasoning, summarization, Q&A, and content generation

  • Expertise in prompt engineering, prompt optimization, and systematic prompt evaluation

  • Ability to generate structured and deterministic outputs for downstream consumption

  • Apply grounding, response validation, and hallucination mitigation techniques

Multi Agent Orchestration & LangGraph (Must Have)

  • Strong hands on experience designing and implementing multi agent AI systems

  • Practical experience working with agent orchestration frameworks, specifically LangGraph

  • Design and implement:

o Orchestrator / supervisor agent patterns o Intent routing, task decomposition, and agent sequencing o Dependency management and agent handoffs

  • Implement tool calling patterns, shared context management, and output aggregation across agents

  • Experience managing agent state, memory, and execution flow in production environments

Retrieval Augmented Generation (RAG)

  • Build and optimize RAG pipelines across large unstructured datasets

  • Hands on experience with:

o Embedding strategies o Vector databases and semantic search o Chunking, ranking, and metadata based retrieval

  • Ensure responses are traceable, explainable, and source grounded

AI Application Engineering

  • Strong backend engineering skills using Python

  • Design modular, API first AI services using scalable architectures

  • Integrate AI services with external systems and tools via secure APIs

  • Efficient handling of long running agent workflows and asynchronous execution


Cloud Native AI & Platform Skills

  • Experience deploying AI solutions on cloud native platforms

  • Familiarity with:

o Containerized AI workloads o CI/CD pipelines for AI and agent services o Scalable, fault tolerant system design

  • Experience managing structured and unstructured data storage for AI workloads

AI Governance, Security & Reliability

  • Implement guardrails and safety controls, including, * Strong experience as a Senior AI / GenAI Engineer

  • Proven, hands on experience with multi agent orchestration using LangGraph

  • Advanced knowledge of:

o LLMs and agentic AI systems o RAG architectures o Python based AI development

  • Experience delivering production grade AI systems, not just experiments

Preferred Qualifications

  • Experience designing large scale agent based platforms

  • Exposure to LLMOps / MLOps practices

  • Familiarity with model and agent evaluation techniques

  • Experience working in regulated or security sensitive environments, Qualifications : BACHELOR OF COMPUTER SCIENCE

Benefits & conditions

Pulled from the full job description

  • Pet insurance
  • Health insurance
  • Vision insurance
  • Dental insurance
  • Commuter assistance, Salary Range: $150,000-$170,000 a year TCS Employee Benefits Summary: Discretionary Annual Incentive. Comprehensive Medical Coverage: Medical & Health, Dental & Vision, Disability Planning & Insurance, Pet Insurance Plans. Family Support: Maternal & Parental Leaves. Insurance Options: Auto & Home Insurance, Identity Theft Protection. Convenience & Professional Growth: Commuter Benefits & Certification & amp; Training Reimbursement. Time Off: Vacation, Time Off, Sick Leave & Holidays.

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