Job Description :

As our AI Automations Specialist, you’ll be embedded directly with clients as a forward-deployed engineer - their primary technical point of contact for understanding, designing, and delivering intelligent automation solutions. You’ll own the full lifecycle: from the first process mapping session to production deployment and beyond.

You’ll work closely with our team lead and account managers to architect solutions, and you’ll be a key voice in how we evolve our product and internal systems over time.

This role is equal parts engineering, consulting, and strategic thinking. If you thrive at the intersection of all three, keep reading.

Client Engagement & Discovery

- Lead process flow mapping sessions with clients to identify bottlenecks, inefficiencies, and automation opportunities

- Engage with stakeholders at all levels - from ops teams to C-suite -with professionalism and clarity

- Navigate client platforms confidently: understand what data exists, what outputs are achievable, and what constraints apply

- Proactively liaise with third-party vendors and platform providers on behalf of clients when needed

Architecture & Engineering

- Co-design automation architectures with the team lead and account managers, balancing technical depth with business pragmatism

- Own all phases of the automation lifecycle - scoping, design, build, testing, deployment, and scaling

- Make well-reasoned trade-off calls across privacy, memory, latency, and cost, and communicate those decisions clearly to both technical and non-technical audiences

- Apply strong AI engineering fundamentals across the full stack: LLMs, agents, RAG, prompt engineering, tool use, orchestration, and evaluation

Internal Contribution

- Contribute to product strategy and development based on bandwidth and evolving company priorities

- Support the design and improvement of internal systems and tooling - Share learnings from client engagements that inform how we build and position our product

Requirements :

- 2–4 years of experience in AI engineering, automation engineering, or a closely related technical role

- Demonstrable experience designing and deploying AI-powered automations in real-world environments

- Strong understanding of modern AI engineering - LLMs, agents, orchestration frameworks (e.g. LangChain, LlamaIndex, n8n, Make, or similar), APIs, and cloud infrastructure

- Comfort navigating and integrating with enterprise platforms and evaluating their data and output capabilities

- Ability to communicate technical concepts clearly to non-technical stakeholders

- Experience reasoning about and articulating trade-offs across privacy, latency, memory, and cost

- Genuinely proactive - you flag issues early, take ownership without being asked, and follow through

- Comfortable operating independently in a fast-paced, ambiguous startup environment - Strong written and verbal communication; open, direct, and collegial with teammates

Nice-to-Haves

- Experience with legal case management platforms, particularly Smokeball, Actionstep, LEAP, or Clio

- Practical understanding of the differences between small-scale and enterprise-level automations - including how architectural decisions, tooling choices, and scaling strategies shift between the two

- Prior experience in a client-facing or forward-deployed engineering role

- Exposure to product development cycles and contributing to product strategy - Familiarity with compliance and data governance considerations in enterprise contexts