Sr. Software Engineer, AI Specialist

We are seeking an accomplished, hands-on Senior Software Engineer to lead the design and implementation of core artificial intelligence capabilities within our Intelligent Data Analytics Platform, with a particular emphasis on multi-agent orchestration and semantic search. This position is intended for a highly capable individual contributor who is able to operate effectively at both architectural and implementation levels - an engineer who anchors the team technically by producing production-grade code, resolving the most demanding problems, and establishing engineering standards by example.

The successful candidate will serve as a principal contributor to an AI-first platform that enables users to explore, query, and analyze enterprise Big Query data through agentic tools and capabilities.

Senior Software Engineer / AI Engineer for Ford Enterprise Data Platform (EDP) Ford Motor Company is a global technology leader for which data serves as the engine of our ongoing transformation. As a data-centric organization, we make data-driven decisions at every level of the enterprise, leveraging the power of artificial intelligence to address complex cost and quality challenges at significant scale.

Within the Enterprise Data Platform (EDP), our mandate extends beyond data management; we are engineering the intelligent systems that will define the future of mobility. We invite candidates who wish to contribute to an environment in which their work directly influences the efficiency and quality of millions of vehicles to consider a career with Ford.

1. Architecture and System Design

* Contribute to the design of scalable, multi-agent AI architectures.

* Design components and modules across agent orchestration, tool systems, and large language model (LLM) integration.

* Evaluate trade-offs across architectural choices (e.g., single- versus multi-agent designs, retrieval-augmented generation versus fine-tuning, deterministic versus probabilistic pipelines).

* Participate in design reviews and contribute to Architecture Decision Records (ADRs).

2. Hands-On Engineering and Execution

* Produce production-grade code across agent frameworks, backend APIs, and frontend interfaces on a daily basis.

* Develop and evolve reusable AI components, including agent tools, embedding pipelines, and evaluation frameworks.

* Implement LLM-powered workflows, including natural-language-to-SQL generation, semantic search, and metadata enrichment.

* Develop services that enable intelligent data access, such as vector search, hybrid retrieval, and query scope management.

* Implement guardrails, validation layers, and observability mechanisms for AI-generated outputs.

3. Full-Stack Development

* Build performant backend services (Python/ FastAPI) and interactive frontend applications (Angular/React) for data exploration.

* Develop both conversational (chat) and structured (API) interfaces for analytical workloads.

* Construct evaluation and benchmarking tooling to support continuous measurement of AI quality.

* Assume end-to-end ownership of features, from initial design through deployment and ongoing monitoring.

4. Semantic Search and Embeddings

* Implement vector embedding pipelines for metadata discovery using pgvector.

* Develop semantic retrieval capabilities across datasets, tables, and columns, employing hybrid search strategies.

* Optimize search relevance through embedding strategies, re-ranking, and rigorous evaluation metrics.

* Contribute to the platform's data quality and governance capabilities.

5. Engineering Excellence

* Produce clean, maintainable, and scalable code that adheres to industry best practices.

* Participate actively in code reviews and establish quality standards through exemplary personal contributions.

* Conduct root-cause analysis on agent failures and implement systematic remediations.

* Serve as the team's technical anchor and primary point of reference for complex implementation challenges.

6. Collaboration

* Partner with Product, Data Engineering, and Platform teams to ensure successful feature delivery.

* Support colleagues through pair programming, knowledge sharing, and technical mentorship.

* Contribute to sprint planning, effort estimation, and technical feasibility assessments.

* Assist in onboarding new team members and disseminating domain expertise across the organization.

1. Architecture and System Design

Contribute to the design of scalable, multi-agent AI architectures.

Design components and modules across agent orchestration, tool systems, and large language model (LLM) integration.

Evaluate trade-offs across architectural choices (e.g., single- versus multi-agent designs, retrieval-augmented generation versus fine-tuning, deterministic versus probabilistic pipelines).

Participate in design reviews and contribute to Architecture Decision Records (ADRs).

2. Hands-On Engineering and Execution

Produce production-grade code across agent frameworks, backend APIs, and frontend interfaces on a daily basis.

Develop and evolve reusable AI…