Lead ML Engineer: Agentic AI & Knowledge Graphs

Spectraforce Technologies; Newark (NJ); On-site; USD 120,000 - 170,000; Full time

Job summary

Spectraforce Technologies is seeking a Lead Machine Learning Engineer to guide the development of agentic AI systems and collaborate with data scientists and engineers.

You will architect AI capabilities, combine LLMs with knowledge graphs, and deploy scalable ML models in cloud environments while promoting best practices in CI/CD, governance, and explainability. Strong leadership and communication are essential.

Qualifications

• Bachelor in Computer Science or Engineering or related field.
• Ability to coach others with minimal guidance and leverage diverse ideas.
• Experience with agile development methodologies and Specification-Driven Development (SDD).
• Knowledge of business concepts, tools and processes for making sound decisions.
• Ability to learn new skills and knowledge on an ongoing basis through self-initiative.
• Excellent problem-solving, communication, and collaboration skills.

Responsibilities

• Architect, Design and, develop, and deploy ML models and Agentic AI systems that solve real-world business problems, while working in collaboration with the Product and Data Science teams; remove complex technical impediments
• Design and implement semantic knowledge layers that represent domain entities, relationships, taxonomies, ontologies, and business rules for use by LLM and agentic applications.
• Build knowledge graph and Graph RAG capabilities that combine vector retrieval with entity resolution, graph traversal, multi-hop reasoning, and relationship-aware context retrieval.
• Solve complex problems by writing and testing application code, developing and validating ML models and Agentic AI, and automating tests and deployment using LLM tools like Claude Code.
• Leverage cloud-based architectures and technologies to deliver optimized ML models, semantic reasoning, and Agentic systems at scale.
• Construct optimized data, ingestion, knowledge graph, semantic layer, and memory pipelines to feed ML models and Agentic systems
• Define approaches for ontology lifecycle management, schema evolution, temporal knowledge, data lineage, graph freshness, and synchronization with source systems.
• Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code
• Bring a strong understanding of relevant and emerging technologies, provide input and coach team members, and embed learning and innovation in the day-to-day
• Work on complex problems in which analysis of situations or data requires an evaluation of intangible variables.
• Use programming languages including but not limited to Python, C++, SQL, Cypher, Gremlin, or other graph query languages.

Skills

Leadership

Coaching

Agile development

Communication

Collaboration

Self-learning

Education

Bachelor's in CS/Engineering or related field

Tools

TensorFlow

PyTorch

scikit-learn

Cypher

Gremlin

GitHub Actions

Jenkins

SageMaker

Job description

Spectraforce Technologies is seeking a Lead Machine Learning Engineer to guide the development of agentic AI systems and collaborate with data scientists and engineers.

You will architect AI capabilities, combine LLMs with knowledge graphs, and deploy scalable ML models in cloud environments while promoting best practices in CI/CD, governance, and explainability. Strong leadership and communication are essential.