[Hiring] Applied AI-Agent Engineer @Sapience AI Corporation

Role Description

This role turns AI capability into product behavior members can rely on. You build the applied AI and agentic systems that let MINERVA understand a request, reason over a community’s knowledge, and take useful action.

You work where models, retrieval, reasoning, and tools come together: designing agents, grounding them in the KO graph and the COGENT architecture, and making them dependable enough for real communities.

You sit between product and the deeper AI stack, and you are the person who makes the platform actually do the intelligent thing, well and safely.

What you will own (Areas of Responsibility)

• Agentic systems: Design and build the agents that let MINERVA understand requests, reason, and take action. Own orchestration, planning, and tool use, and keep it dependable. Design for the limits of models, not just their strengths.
• Grounding and retrieval: Ground agent behavior in the KO graph and the COGENT architecture so answers rest on real community knowledge. Build retrieval that surfaces the right knowledge at the right time. Reduce confident errors through grounding and verification.
• Reasoning integration: Integrate neural and symbolic reasoning into applied behavior in partnership with neuro-symbolic AI. Decide where a model should reason and where structure should carry the load. Turn reasoning advances into product behavior.
• Tooling, actions, and integrations: Build the tools and actions agents use, including safe access to systems and data. Make actions reliable, observable, and reversible where they should be. Connect applied AI to the systems a community already runs.
• Trust, safety, and guardrails: Build the guardrails that keep agent behavior safe and within bounds. Handle uncertainty honestly, and make provenance visible. Treat member trust as a design constraint.
• Evaluation and iteration: Build evaluation for agent quality, including accuracy, groundedness, and safety. Instrument applied systems so you can tell whether they are working in production. Iterate on real behavior, not just offline tests.
• Productionization and reliability: Take applied AI from prototype to dependable production, in partnership with ML infrastructure. Balance capability against latency, cost, and reliability. Own the behavior members experience, not just the demo.

What this role is not

• This is not a model research role.
• This is not an infrastructure role.
• This is not a prototype-only role.
• This is not a hype-driven role.

What success looks like

• Useful agents: Members get systems that understand, reason, and act reliably on their knowledge.
• Grounded answers: Behavior rests on real community knowledge, with fewer confident errors.
• Safe by design: Guardrails keep behavior within bounds, and uncertainty is handled honestly.
• Dependable in production: Applied systems hold up under real use, latency, and cost.
• Measured quality: Agent quality is evaluated and improving on real behavior.
• Reasoning realized: Advances in COGENT show up as better product behavior.

Qualifications

• Five or more years in software engineering, with strong recent work in applied AI or ML.
• Hands-on experience building agentic systems, LLM applications, or retrieval-augmented systems in production.
• Strong understanding of grounding, tool use, and the limits of models.
• Experience making AI behavior safe, reliable, and observable.
• Strong Python, plus solid software engineering fundamentals.
• Rigor about evaluation and honest handling of uncertainty.
• Care for member trust and safety.

Preferred qualifications

• Experience with agent frameworks, orchestration, and planning.
• Familiarity with knowledge graphs and neuro-symbolic reasoning.
• Experience with retrieval, embeddings, and hybrid search.
• Experience productionizing AI features at scale.
• Domain understanding of professional or knowledge-intensive communities.

How you work

• You name the real problem before reaching for a model or an agent.
• You are honest about what works, what does not, and what it will take.
• You treat grounding, safety, and trust as design constraints.
• You build systems that are dependable, not just impressive.
• You measure real behavior and iterate on evidence.

Skills & Competencies

• Agent design, orchestration, planning, and tool use.
• Grounding, retrieval, and reducing confident errors.
• Integrating neural and symbolic reasoning into applied behavior.
• Guardrails, safety, and provenance.
• Evaluation and instrumentation of AI behavior.
• Productionizing AI features reliably.
• Software engineering fundamentals for AI systems.

Services & Tools Experience

• LLM application and agent frameworks, plus orchestration tooling.
• Retrieval frameworks, vector databases, and graph access.
• Python as the primary language, plus TypeScript where needed.
• Evaluation and experiment-tracking tooling.
• Observability for AI behavior in production.
• Cloud platforms and containers.
• Building applied behavior on the MINERVA platform, KO graph, and COGENT architecture.

Prior Experience & Background

• Prior applied AI, ML engineering, or agent engineering at a software or AI company.
• A track record of shipping AI features that people actually rely on.
• Experience making AI behavior safe and dependable in production.
• Experience with grounding and retrieval systems is a plus.

Cross-functional partners

You work most closely with Product, Neuro-Symbolic AI, Knowledge Graph Engineering, ML Infrastructure, and Research. You turn the COGENT architecture and the KO graph into dependable applied behavior inside MINERVA.

How we hire

We review every application, and we encourage you to apply even if you do not match every line above. Research shows that talented people, especially those from underrepresented communities, often hold back when they do not meet every qualification. If that is the only thing holding you back, apply anyway.

Sapience AI is an equal opportunity employer. We are committed to a workplace where everyone, regardless of background, has a voice in building what comes next.

Compensation

• Base Salary: $204,000 - $216,000 + early stage equity
• Generous health and wellness benefits