We are looking for a hands-on Tech Anchor / Senior Software Engineer to drive the design and implementation of core AI capabilities within our Intelligent Data Analytics Platform (Lightspeed), spanning multi-agent orchestration, natural language-to-SQL generation, and semantic data discovery. This role is for a strong individual contributor who can operate at both architectural and implementation depth — someone who anchors the team technically by writing production-grade code, solving the hardest problems, and setting engineering standards through example.
You will be a key contributor to an AI-first platform that enables users to explore, query, and analyze enterprise BigQuery data through natural language — reliably, accurately, and at scale.
Responsibilities1. Architecture & System Design
- Contribute to the design of scalable, multi-agent AI architectures for data discovery and query generation
- Design components and modules across agent orchestration, tool systems, and LLM integration
- Evaluate trade-offs across design choices (e.g., single vs multi-agent, RAG vs fine-tuning, deterministic vs probabilistic pipelines)
- Participate in design reviews and contribute to architecture decision records (ADRs)
2. Hands-On Engineering & Execution
- Write production-grade code across agent frameworks, backend APIs, and frontend interfaces daily
- Build and evolve reusable AI components (agent tools, embedding pipelines, evaluation frameworks)
- Implement LLM-powered workflows including NL-to-SQL generation, semantic search, and metadata enrichment
- Develop services enabling intelligent data access (vector search, hybrid retrieval, query scope management)
- Implement guardrails, validation layers, and observability for AI-generated outputs
3. Full Stack Development
- Build performant backend services (Python/FastAPI) and interactive frontends (Angular/React) for data exploration
- Develop both conversational (chat) and structured (API) interfaces for analytics
- Build evaluation and benchmarking tooling for continuous AI quality measurement
- Own features end-to-end from design through deployment and monitoring
4. Semantic Search & Embeddings
- Implement vector embedding pipelines for metadata discovery (pgvector)
- Build semantic retrieval across datasets, tables, and columns with hybrid search strategies
- Optimize search relevance through embedding strategies, re-ranking, and evaluation metrics
- Contribute to data quality and governance capabilities within the platform
5. Engineering Excellence
- Write clean, maintainable, and scalable code following best practices (SOLID, DRY, design patterns)
- Actively participate in code reviews and set quality standards through your own contributions
- Perform root cause analysis on agent failures and implement systematic fixes
- Anchor the team technically — be the go-to person for complex implementation challenges
6. Collaboration
- Partner with Product, Data Engineering, and Platform teams on feature delivery
- Support teammates through pair programming, knowledge sharing, and technical guidance
- Contribute to sprint planning, estimation, and technical feasibility assessments
- Help onboard new team members and share domain expertise
What We're Looking For
- 6+ years of professional software engineering with strong hands-on coding ability
- Experience building AI-powered applications or working with LLM-based systems in production
- Ability to take ambiguous requirements and deliver working, tested software independently
- Strong debugging and problem-solving skills across the full stack
- Track record of owning and delivering complex features end-to-end
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Technology Stack
- Programming: Python (primary), Java, TypeScript, Angular/React
- AI/ML: Google ADK, LangChain/LangGraph, OpenAI/Gemini APIs, prompt engineering, RAG pipelines
- Data & Cloud: GCP (BigQuery, Vertex AI, Cloud Run preferred)
- Backend: FastAPI, Pydantic, SQLModel/SQLAlchemy, PostgreSQL (pgvector)
- Frontend: Angular or React, TypeScript
- CI/CD & Infra: Terraform, GitHub Actions, Docker
- Evaluation: Custom eval frameworks, LLM-as-judge patterns
- Tools: Git, Alembic
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Nice to Have
- Experience with Google Agent Development Kit (ADK) or similar agent frameworks (AutoGen, CrewAI, LangGraph)
- Exposure to NL-to-SQL or text-to-code generation systems
- Knowledge of ML fundamentals — embeddings, classification, clustering, evaluation metrics
- Experience with vector databases and semantic retrieval optimization
- Familiarity with data governance (metadata management, lineage, data quality)
- Experience building developer tooling or platform SDKs
Skills Required
- 6+ years of professional software engineering experience with strong hands-on coding ability
- Experience building AI-powered applications or working with LLM-based systems in production
- Ability to take ambiguous requirements and independently deliver working, tested software
- Strong debugging and problem-solving skills across the full stack
- Track record of owning and delivering complex features end-to-end
- Experience with Google Agent Development Kit or a similar agent framework such as AutoGen, CrewAI, or LangGraph
- Exposure to natural-language-to-SQL or text-to-code generation systems
- Knowledge of machine learning fundamentals, including embeddings, classification, clustering, and evaluation metrics
- Experience with vector databases and semantic retrieval optimization
- Familiarity with data governance, metadata management, data lineage, or data quality
- Experience building developer tooling or platform SDKs
Ford Motor Company Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Ford Motor Company and has not been reviewed or approved by Ford Motor Company.
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Healthcare Strength — Medical, dental, and vision coverage start on day one with options that include zero-premium plans, free mental health support, and wellness resources. For represented hourly employees, health plans are described as low-cost with strong coverage value.
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Retirement Support — A 401(k) with company match and additional company contributions is available from day one, alongside life and disability coverage. Pension eligibility in certain situations and financial-planning support reinforce long‑term security.
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Parental & Family Support — Paid parental leave, fertility, surrogacy, and adoption benefits, plus a ramp‑up program for returning parents, reflect a family‑focused package. Flexible Family Care days and generous time‑off options help address short‑term caregiving and personal needs.
Ford Motor Company Insights
What We Do
Ford is a global company with shared ideals and a deep sense of family. From our earliest days as a pioneer of modern transportation, we have sought to make the world a better place – one that benefits lives, communities and the planet. We are here to provide the means for every person to move and pursue their dreams, serving as a bridge between personal freedom and the future of mobility. In that pursuit, our 186,000 employees around the world help to set the pace of innovation every day.
