Forward Deployed AI Engineer

What if you could help shape how AI changes the way work gets done across Locus?

As a Forward Deployed AI Engineer, you’ll partner directly with teams across Locus Robotics organization to identify where AI can eliminate manual work, simplify complex processes, and make employees more productive. You’ll turn real business challenges into AI agents, intelligent applications, and automated workflows that employees use every day.

You’ll work side-by-side with internal stakeholders to understand how they work today, uncover opportunities to do things better, and rapidly build and deploy solutions that connect with our enterprise systems. And when something works, you’ll help turn it into a reusable approach that can benefit teams across the company.

This is a hands-on enterprise AI development role focused on internal business transformation, not Locus product development or AI model research. We’re looking for a strong software builder who enjoys solving real-world business problems, working directly with users, and taking ideas from concept to production. You’ll also help ensure the AI solutions we build are secure, reliable, measurable, and designed for responsible enterprise use.

Responsibilities

• Work directly with teams across Locus to understand how work gets done today, identify high-value opportunities for AI, and determine where AI can meaningfully improve the workflow, transforming manual and complex processes into smarter, faster, and more efficient ways of working.
• Translate loosely defined business challenges into practical AI solutions, moving quickly from concept and prototype to secure, production-ready tools and workflows.
• Design, build, and deploy AI agents, assistants, and automated workflows using large language models, retrieval, tool integrations, structured outputs, and appropriate human oversight.
• Build secure, reliable integrations that connect AI solutions with enterprise systems and data using APIs, connectors, MCP, and other appropriate integration methods.
• Build retrieval and grounding capabilities that enable AI solutions to securely access and use structured and unstructured enterprise data, leveraging ingestion, metadata, embeddings, search, and reranking techniques as appropriate.
• Ensure AI solutions are secure, reliable, and enterprise-ready by incorporating authentication, authorization, audit logging, observability, cost controls, and human-in-the-loop safeguards in partnership with IT, Security, and governance teams.
• Take solutions beyond the prototype by building automated evaluations and regression testing, supporting deployment and monitoring, and continuously improving performance, reliability, cost, and user outcomes.
• Measure the impact of AI solutions through business outcomes such as reduced cycle time, hours saved, improved quality, increased capacity, and better customer outcomes.
• Turn successful implementations into reusable components, templates, reference architectures, and documented patterns that accelerate AI adoption across Locus Robotics.
• Stay current with emerging AI models, agent frameworks, integration standards, and enterprise AI practices, while sharing knowledge and helping teams successfully adopt approved AI capabilities.

Qualifications

• Bachelor's degree in computer science, engineering, or related technical discipline.
• 4+ years of professional software engineering experience building, deploying, and supporting production applications.
• Strong proficiency in Python, with a track record of building APIs, integrations and automation that connect applications with enterprise systems and data.
• Hands-on expertise with large language models, commercial or open model APIs, and the development of AI agents and agentic workflows.
• Proven ability to build and deploy enterprise AI agents or agentic workflows using platforms such as Glean, Claude, or comparable enterprise AI, agent and orchestration platforms
• Ability to partner directly with business stakeholders, translate ambiguous needs into practical technical solutions, and iterate quickly based on user feedback.
• Working knowledge of retrieval-augmented generation (RAG), including embeddings, semantic or hybrid search, prompt and context engineering, and structured model outputs.
• Demonstrated success integrating enterprise platforms such as Microsoft 365, Salesforce, Slack, Jira, Confluence, ERP systems, and modern data platforms.
• Strong understanding of enterprise application security, including authentication, authorization, OAuth/OIDC, role-based access controls, and permission-aware data access.
• Familiarity with MCP or similar standards for securely connecting AI models and agents with enterprise tools, systems, and data.
• Knowledge of vector databases, enterprise search, and knowledge retrieval systems.
• Proficiency with modern software engineering practices, including automated testing, version control, CI/CD, application observability, and production support.
• Demonstrated ownership and sound judgment, with the ability to work effectively across teams and organizational boundaries.
• Excellent written and verbal English communication skills, with the ability to clearly explain technical concepts and tradeoffs to both technical and non-technical audiences.

The expected base salary range for this role is $150,000 - $200,000 annually, based on external market data, plus bonus and equity. Actual offers will depend on factors such as the candidate’s experience, education, training, key or critical skills, geographic location, and current market and business conditions