AI Engineer

TechDigital Group; Earth (TX); On-site; USD 120,000 - 210,000; Full time

Job summary

TechDigital Group is seeking an AI Solutions Architect to embed with client domain teams and identify high-value AI opportunities, validating feasibility before solutioning.

You will design, build, and deploy AI agents using agentic frameworks, develop RAG pipelines, and integrate AI solutions with client enterprise systems while communicating trade-offs to non-technical stakeholders.

Qualifications

• 3-5 years of experience in AI/ML roles.
• Master’s degree in CS or related field; PhD preferred.
• Strong production-grade Python programming skills; deployable AI apps.

Responsibilities

• Embed with client domain teams to identify AI opportunities and validate feasibility.
• Design, build, and deploy AI agents with robust tool use and error handling.
• Build RAG pipelines grounded in client data and memory architectures.
• Integrate AI solutions with client systems via APIs and gateways.
• Define success metrics and establish continuous benchmarking and quality monitoring.
• Partner with clients, conduct workshops, and drive AI adoption and enablement on the ground.

Skills

Experience 3-5 years

Python

LLMs

Prompt engineering

Agentic workflows

Education

Master’s degree in Computer Science

PhD preferred

Tools

LangGraph

LangChain

CrewAI

Google ADK

REST APIs

AWS/Azure/GCP

Docker

Git

Job description

JD:

• Embed with client domain teams to identify high-value AI opportunities, map pain points to platform capabilities, and validate feasibility before solutioning.


• Design, build, and deploy AI agents using agentic frameworks (LangGraph, CrewAI, Google ADK) with tool use, memory, structured outputs, and error recovery.


• Build retrieval-augmented generation (RAG) pipelines grounded in client enterprise data — designing context engineering and memory architectures for multi-turn and multi-agent workflows.


• Integrate AI solutions with client enterprise systems via APIs, MCP tool gateways, CRM, billing, and operational platforms — handling authentication, rate limiting, and production-grade error handling.


• Define success metrics in partnership with client stakeholders, build evaluation harnesses, and establish continuous benchmarking and quality monitoring for deployed AI systems.


• Serve as a trusted technical partner to client teams — run workshops, pair-program with domain engineers, and drive AI adoption and enablement on the ground.


• Surface platform gaps, friction, and feature requests back to Cognizant's AI architecture and engineering teams to improve reusable offerings.

Must Have's:

• 3-5 yrs experience


• Master’s degree in Computer Science, Artificial Intelligence, Data Science, or a related field with 1–3 years of relevant experience. PhD preferred.


• Strong production-grade Python programming skills — not notebook-grade; experience building deployable, maintainable AI applications.


• Hands‑on experience with LLMs (GPT, Claude, Gemini), prompt engineering, structured outputs, function calling, and agentic workflow design.


• Experience designing and deploying RAG pipelines — embeddings, vector databases, reranking, hybrid search, and retrieval optimization.


• Familiarity with agentic AI frameworks such as LangGraph, LangChain, CrewAI, Google ADK, or similar orchestration tools.


• Working knowledge of REST APIs, cloud platforms (AWS, Azure, or GCP), Git, Docker, and modern software development practices.


• Strong analytical, problem‑solving, and communication skills with the ability to explain AI trade-offs to non-technical stakeholders.


• Consultative mindset — comfortable operating in ambiguous environments, discovering problems, and defining approaches independently.