Software Engineer (AI)

Zensar•Lansing, MI

3d•$83,728 - $129,027•Onsite

About The Position

Zensar is hiring a Graduate Software Engineer for its AI Platform Development team in the United States. The team designs and builds custom AI platforms for Zensar and its clients, deploying them on major cloud providers or in client environments. The role combines platform development with forward-deployed client work and requires understanding AI models, agents, and decision models, as well as engineering reliable systems around them. The engineer will build end-to-end platform features, including services, APIs, web interfaces, data components, and tests; develop AI agents and safeguards such as prompts, tools, retrieval, evaluations, human approval, and audit trails; and contribute to the product roadmap from feature proposal through release. The role also includes using AI coding assistants, deploying platforms in client clouds or data centres, integrating with client systems, adapting platforms to client needs, and communicating technical decisions through demos, pilots, and handovers. The position is full-time and described as San Jose, California, 100% onsite/hybrid. Zensar offers benefits and professional growth opportunities. The company describes flexible work arrangements and a competitive benefits package that includes medical, dental, vision, and 401(k).

Requirements

Strong Python skills and TypeScript or JavaScript skills.
Knowledge of APIs (HTTP, REST, JSON, and OAuth basics) and SQL databases.
Experience with Linux, shell, Docker, Git, and GitHub.
Cloud skills covering compute, storage, networking, identity, and infrastructure as code on at least one of AWS, Azure, Google Cloud, or Oracle Cloud.
Understanding of large language models, embeddings, prompting, fine-tuning basics, and model limitations.
Understanding of agent planning, tool use, memory, and retrieval, with at least one agent built.
Understanding of decision models, including rules, scoring, and machine-learning classifiers, and how to evaluate and explain them.
Clear communication with clients and willingness to work at client sites and travel.
A BS or MS in Computer Science, Computer Engineering, or a related field from a strong US university; applicants should be graduating in 2025 or 2026 with a strong academic record.
A GitHub profile or portfolio with real projects beyond coursework.
Strong writing skills, including the ability to explain a design on one page and a decision in one paragraph.
Ability to own outcomes, learn quickly, work with open problems, and switch between platform development and client-team work.

Nice To Haves

React and FastAPI or a similar framework.
Kubernetes, Terraform, and CI/CD pipelines.
Agent frameworks and protocols such as LangGraph and MCP, vector search, and knowledge graphs.
Experience evaluating model outputs using test sets, metrics, and red-teaming.
Networking and systems fundamentals, including DNS, TLS, load balancers, and monitoring.
Security fundamentals, including OWASP Top 10 and secrets management.
A cloud certification from any provider.
Internships, open-source work, hackathons, or a project that other people have used.

Responsibilities

Build end-to-end platform features, including services, APIs, web interfaces, data, and tests.
Build AI agents and associated controls, including prompts, tools, retrieval, evaluations, human approval, and audit trails.
Understand the roadmap, propose features, and take them from idea to release.
Use AI coding assistants by writing clear specifications, reviewing their output, and owning the resulting work.
Deploy platforms into client cloud environments or data centres and integrate them with client systems and APIs.
Work with client teams, adapt platforms to their needs, and bring lessons back into the product.
Run demos, pilots, and handovers, and explain technical choices to engineers and managers.
Work in both platform-building and forward-deployed client settings as needed.