AI Engineer

Jacobs

San Diego, UShybrid$100k-$120k/yrPosted Jul 17, 2026
Posting intelligenceActively listed

Skills

javascripttypescriptlangchainexpressdockerpodmangithubpythonopenaiflaskazurereactcicdcssllm

About the role

Location

San Diego, California, United States

Capabilities

Digital and Data

Office Setup

Hybrid

Job ID

#42414

Industry

National Security & Defense

At Jacobs, we're challenging today to reinvent tomorrow by solving the world's most critical problems for thriving cities, resilient environments, mission-critical outcomes, operational advancement, scientific discovery and cutting-edge manufacturing, turning abstract ideas into realities that transform the world for good.

Your impact

We're looking for a junior-level AI developer with a solid software engineering foundation and a drive to build and deploy AI-powered applications that support solutions across the business for both government and private-sector clients. The ideal candidate is a developer who's eager to build, iterate, and ship AI-powered tools and applications, and who wants to grow into a leading voice on our AI Engineering team. They should be comfortable using AI coding assistants (Claude, OpenAI Codex, Cursor), familiar with agentic AI frameworks and orchestration patterns, and ready to build depth working across the full stack. In addition, the ideal candidate will possess a degree in computer science, AI, data science, engineering, or similar domain areas.

The chosen candidate will become a member of the Digital and Data team at Jacobs, helping drive innovation in technical project work for our clients in collaboration with subject matter experts, technologists, engineers, data scientists, project managers, and more.

Here's what you'll need

Design, develop, and deploy AI-powered applications and tools using Python, TypeScript/JavaScript, and modern AI frameworks (LangChain, LangGraph, CrewAI, PydanticAI or similar)

Build and configure MCP (Model Context Protocol) servers and integrations to connect AI models with enterprise data sources, APIs, and tooling

Develop RAG (Retrieval-Augmented Generation) pipelines, agentic workflows, and AI-assisted automation solutions for internal and client-facing projects

Leverage AI-assisted development tools (Claude, Codex, Cursor, GitHub Copilot) to accelerate delivery and maintain high code quality

Collaborate cross-functionally with subject matter experts, data engineers, and project managers to translate business requirements into production-ready AI solutions

Contribute to full-stack solutions builds including front-end interfaces (React, HTML/CSS/JS), back-end APIs, and cloud-hosted AI services

Evaluate, integrate, and maintain AI platforms, APIs, and toolchains as the technology landscape evolves

Contribute to technical presentations, demos, and documentation for both internal teams and external clients

Participate in knowledge sharing, code reviews, and mentoring across teams and domains

Stay current with rapidly evolving AI tools, models, and best practices; proactively bring new capabilities to the team

What You'll Need:

1-3 years of experience in software development

Bachelor's degree in computer science, software engineering, AI, data science, or similar domain

Demonstrated proficiency building applications with AI/LLM APIs and frameworks

o Anthropic Claude API, OpenAI API, LangChain/LangGraph, Model Context Protocol (MCP), or similar

Strong proficiency in Python and JavaScript/TypeScript; working knowledge of SQL

Experience version control (GitHub), and CI/CD pipelines.

Familiarity with containerization (Docker or Podman),

Proven ability to use AI-assisted coding tools (Claude, Codex, Cursor, GitHub Copilot) to accelerate development workflows

Ability to travel, as necessary, to meet project and client requirements

Preferred:

Experience in the AEC industry

Experience developing and deploying RESTful APIs and backend services using frameworks such as FastAPI, Flask, or Express

Hands-on experience building RAG pipelines, including document ingestion, chunking strategies, embedding models, vector stores (Pinecone, Weaviate, pgvector, etc.), and retrieval optimization

Technical proficiency with cloud platforms and data infrastructure such as Microsoft Azure, Microsoft Fabric, Google Cloud, Amazon Web Services, Power BI, GIS, and database technologies (data lakes, vector databases, etc.)

Posted Salary Range: Minimum

100,000.00

Posted Salary Range: Upper

120,000.00

Our health and welfare benefits are designed to invest in you, and in the things you care about. Your health. Your well-being. Your security. Your future. Employees have access to medical, dental, vision, and basic life insurance, a 401(k) plan, and the ability to purchase company stock at a discount. Eligible employees may also enroll in a deferred compensation plan or the Executive Deferral Plan. Jacobs has an unlimited U.S. Personalized Paid Time Off (PPTO) policy for full-time salaried/exempt employees, seven paid holidays, and caregiver leave. And certain roles may be eligible for additional rewards, including merit increases, performance discretionary bonus, and stock.

The base salary range for this position is $100,000.00 to $120,000.00. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training.

We value collaboration and believe that in-person interactions are crucial for both our culture and client delivery. We empower employees with our hybrid working policy, allowing them to split their work week between Jacobs offices/projects and remote locations enabling them to deliver their best work.

Your application experience is important to us, and we’re keen to adapt to make every interaction even better. If you require further support or reasonable adjustments with regards to the recruitment process (for example, you require the application form in a different format), please contact the team via Careers Support .

Compensation

This Machine Learning Engineer role pays $100k-$120k/yr. Within typical range for machine learning engineer roles in United States.

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