Sr. Software Engineer, AI Specialist

Ford • Dearborn, MI

1d

About The Position

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 BigQuery data through agentic tools and capabilities.

Requirements

• Bachelor’s degree in Computer Science, Engineering, Data Science, or a related technical field.
• 8 + years of professional software engineering experience with demonstrated hands-on coding proficiency.
• Demonstrable experience building AI-powered applications or operating LLM-based systems in production environments.
• Proven ability to interpret ambiguous requirements and independently deliver functional, well-tested software.
• Strong debugging and problem-solving capabilities across the full technology stack.
• A demonstrated record of owning and delivering complex features from inception through completion.
• Programming Languages and Frameworks: Python (primary), Java, JavaScript/TypeScript, Angular/React
• Artificial Intelligence and Machine Learning: Google ADK, LangChain/LangGraph, OpenAI and Gemini APIs, prompt engineering, retrieval augmented generation (RAG) pipelines
• Data and Cloud Infrastructure: Google Cloud Platform (BigQuery, Vertex AI, and Cloud Run preferred)
• Backend Technologies: FastAPI, Pydantic, SQLModel/SQLAlchemy, PostgreSQL with pgvector
• Frontend Technologies: Angular or React, TypeScript
• Continuous Integration, Continuous Delivery, and Infrastructure: Terraform, GitHub Actions, Docker Evaluation: Custom evaluation frameworks, LLM-as-judge methodologies

Nice To Haves

• Experience with the Google Agent Development Kit (ADK) or comparable agent frameworks, such as CrewAI, or LangGraph.
• Applied machine learning experience encompassing embeddings, classification, clustering, natural language processing, and evaluation metrics.
• Demonstrated experience with vector databases and semantic retrieval optimization.
• Familiarity with data engineering practices and data governance processes.
• Prior experience developing internal developer tooling or platform SDKs.

Responsibilities

• 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).
• 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.
• 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.
• 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.
• 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.
• 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.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior