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About the role
Key responsibilities & impact- Design and implement real-world agentic AI systems using modern agent frameworks and orchestration tools.
- Develop agentic workflows that go beyond chat, including complex analytical pipelines, multi-step research workflows, tool-using agents, knowledge-grounded agents, and structured decision-support systems.
- Work with knowledge-based AI architectures, including retrieval-augmented generation, knowledge graphs, symbolic rules, structured domain models, ontologies, and hybrid reasoning systems.
- Develop and apply mechanisms for controlling inference, including planning constraints, reasoning policies, guardrails, validation layers, tool-use control, and human-in-the-loop checkpoints.
- Explore and implement neuro-symbolic approaches for agentic reasoning, combining LLM-based reasoning with symbolic, rule-based, graph-based, or formally structured methods.
- Build transparent AI methods that make agent behaviour traceable, explainable, testable, and auditable.
- Create evaluation and testing frameworks for agentic systems, including benchmark tasks, regression tests, failure-mode analysis, trace inspection, robustness testing, and task-level performance measurement.
- Develop full-stack prototypes and production applications, integrating backend services, APIs, databases, frontend interfaces, model providers, and orchestration layers.
- Collaborate with researchers, engineers, product teams, and domain experts to translate ambiguous real-world problems into reliable agentic workflows.
- Stay current with developments in agentic AI, reasoning systems, LLM orchestration, AI evaluation, and applied neuro-symbolic methods.
Requirements
What you’ll need- Must have neuro symbolic reasoning experience.
- Strong multi-project experience developing real-world AI agents or agentic workflows.
- Demonstrated focus on agentic reasoning, including planning, decomposition, tool use, multi-step inference, workflow execution, or autonomous task completion.
- Experience in either industrial AI development, academic research, or ideally both.
- Hands-on exposure to knowledge-based agentic systems, such as agents grounded in knowledge graphs, structured documents, domain rules, ontologies, databases, or retrieval systems.
- Experience with methods for controlling reasoning or inference, such as guardrails, constrained planning, validation layers, policy-based tool use, symbolic checks, or deterministic workflow components.
- Familiarity with neuro-symbolic AI concepts or hybrid reasoning architectures.
- Experience designing transparent, inspectable, or explainable AI methods.
- Practical experience with agentic reasoning evaluation, testing, benchmarking, observability, or failure analysis.
- Full-stack web development experience, including backend APIs and frontend application development.
Benefits
Comp & perks- Health insurance
- Retirement plans
- Paid time off
- Flexible work arrangements
- Professional development
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
Agent FrameworksAnalytical PipelinesKnowledge GraphsInference Control MechanismsPlanning ConstraintsHybrid Reasoning SystemsBenchmark TestingAPIs DevelopmentFrontend Application DevelopmentDatabase Integration
Soft Skills
CollaborationProblem-Solving