Software Engineer, AI Enablement
$97.14k - $192.9kFord Motor Co
Job Description We are seeking a Senior Software Engineer to design and build AI-powered agents that enable intelligent discovery, recommendation, and management of enterprise ontology assets. The ideal candidate combines strong software engineering skills with practical experience applying AI techniques to solve complex information discovery, recommendation, and search. This individual will evaluate alternative technical approaches, make architecture recommendations, and deliver scalable production solutions. Responsibilities
- Design and build AI-powered applications, agents, and intelligent workflows that improve discovery, recommendation, and management of enterprise ontology and metadata assets.
- Evaluate and recommend technical approaches for semantic search, knowledge management, retrieval, and recommendation challenges.
- Design and implement scalable backend services, APIs, and AI-enabled capabilities.
- Build retrieval, ranking, and recommendation systems that support intelligent user experiences.
- Collaborate with product managers, ontology experts, and domain stakeholders to translate business needs into technical solutions.
- Conduct technical evaluations and proof-of-concepts for emerging AI technologies.
- Drive architecture decisions, engineering best practices, and operational excellence.
- Bachelor's degree in computer science, Information Systems, or a related field.
- 7+ years of professional experience in Data Science or Software Engineering building scalable production systems.
- 5+ years of experience working with Python/Java/Javascript/Angular programming languages.
- Experience in building autonomous agents using agent orchestration frameworks such as LangGraph/LangChain/Google ADK or Similar Technologies.
- Experience implementing tool integration patterns (MCP), agent communication protocols, and AI application observability.
- Experience with vector search or hybrid retrieval architectures.
- Experience working with GCP services (Vertex AI, Cloud Run, and BigQuery) or similar cloud platforms for deploying scalable AI solutions.
- Strong problem-solving and system design skills.
- Ability to evaluate competing technical approaches and articulate tradeoffs.
- Experience working with large, complex datasets and information management systems. Even Better, you may have:
- Experience with semantic technologies, search, recommendation systems, or knowledge graphs.
- Experience working with graph databases, Graph-RAG applications.
- Developing and maintaining Python-based optimization models to support demand elasticity, production planning, and constraint-based decision frameworks.
- Integrating heterogeneous enterprise datasets into structured, analysis-ready pipelines using BigQuery, GCS, and Python.
- Performing data reconciliation, fuzzy matching, and standardization across inconsistent source systems to ensure data quality and analytical integrity.
- Designing and deploying lightweight internal applications (e.g., Dash-based tools) and contributing to containerized deployments to enable business-facing access to decision models.
- Collaborating with cross-functional stakeholders to translate business questions into optimization and analytical frameworks.
- Design, develop, and maintain Python-based optimization models to support demand elasticity, production planning, and constraint-based decision systems.
- Translate complex business problems into structured analytical and optimization frameworks.
- Build and maintain data pipelines using BigQuery, GCS, and Python to integrate heterogeneous enterprise data sources.
- Perform data reconciliation, fuzzy matching, and standardization across inconsistent datasets to ensure analytical integrity.
- Develop lightweight internal applications (e.g., Dash or streamlit) to operationalize analytical outputs for business users.
- Contribute to containerized deployments to support scalable and maintainable delivery of decision tools.
- Partner with cross-functional stakeholders to define requirements and validate outputs.
- Support semantic alignment across systems by contributing to feature definition consistency, cross-system mapping, and ontology-informed data structures.
- Document modeling assumptions, data transformations, and system dependencies to enable reproducibility and reuse.
- Continuously improve model performance, data quality, and deployment efficiency across decision systems.
- Bachelor's degree in Data Science, Engineering, Mathematics, Computer Science, Operations Research, or equivalent field.
- 3+ years of experience developing analytical or optimization models in Python.
- Experience building and maintaining data pipelines using SQL and cloud-based data platforms (e.g., BigQuery, GCS).
- Strong proficiency in Python for data analysis and modeling (e.g., pandas, NumPy, Pyomo or similar optimization libraries).
- Experience integrating and standardizing heterogeneous enterprise datasets.
- Familiarity with containerization concepts (e.g., Docker) and deploying lightweight applications or services in a cloud environment.
- Ability to translate business problems into structured analytical frameworks.
- Strong written and verbal communication skills with experience working cross-functionally.
Vacancy posted 5 days ago
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