Forward Deployed Engineer (FDE) Agentic AI Workflow Automation

Role: Forward Deployed Engineer (FDE) Agentic AI Workflow Automation

Location: New York, NY (Onsite)

Contract on W2 or 1099

Summary:

• Our client, a large global financial services firm, is scaling an enterprise-wide AI transformation program, extending firmwide generative AI infrastructure into autonomous, agentic workflow automation across its non-revenue-generating functions. This includes a firmwide AI access layer already in broad internal use and an active expansion of agentic and autonomous task automation beyond core engineering into operations, research, and finance-adjacent functions.
• These roles are structured as Forward Deployed Engineers (FDEs): rather than sitting centrally and handing designs to divisions, each FDE embeds directly with one or more internal business functions, works side by side with divisional stakeholders to understand their workflows firsthand, and uses agentic AI models to design, build, and iterate automation solutions in place. The FDE owns the full lifecycle within their embedded function discovery, prototyping, deployment, and iteration while feeding reusable patterns back to the broader engineering organization.
• FDEs are expected to help define and prioritize automation opportunities within their embedded function, not solely execute against a pre-existing backlog making this a hands-on, high-autonomy role that blends engineering delivery with direct business partnership.

Role Summary
Embed directly within one or more non-revenue-generating functions to identify, design, build, and iterate agentic AI automations for their highest-value manual workflows. Work hands-on with agentic AI models and orchestration tools to move fast from workflow discovery to a working solution in production, partnering continuously with divisional stakeholders who are often non-technical to refine the solution against real usage. Bring engineering rigor and governance discipline to that work while operating with the speed and adaptability of an embedded, forward-deployed model.
Key Responsibilities:

• Embed with assigned business function(s) to learn their workflows firsthand shadowing end users, reviewing existing processes, and identifying high-value automation candidates in partnership with divisional leadership.
• Design and build agentic AI solutions using existing agentic frameworks and foundation models, favoring rapid prototyping and fast iteration with real users over long design cycles.
• Own delivery end to end within the embedded function: discovery, prototyping, pilot, production deployment, and ongoing iteration based on user feedback.
• Translate ambiguous, often undocumented manual processes as described by non-technical business users into clear automatable workflows and working solutions.
• Apply human-in-the-loop controls and structured, auditable logging so every automated decision is explainable and defensible to regulators and internal audit.
• Continuously gather feedback directly from divisional end users and adjust solutions in near-real-time rather than through a formal ticketing/backlog process.
• Feed successful patterns, reusable components, and lessons learned back to the central engineering organization so other FDEs and functions can reuse them.
• Partner with security and compliance stakeholders as needed to clear solutions for production use within the function.

Required Experience & Qualifications

• Total experience: 8 15+ years in software engineering, with meaningful recent experience building and shipping production AI/ML or agentic systems (not pilots or proofs of concept).
• Forward-deployed / embedded delivery experience: Prior experience working directly embedded with a business function or client as a forward-deployed engineer, solutions engineer, or similarly hands-on customer-facing technical role rather than purely centralized platform engineering.
• Domain background: Prior experience in a large regulated enterprise banking, financial services, insurance, or healthcare where AI systems had to satisfy audit, security, and compliance review before going live.
• Process fluency: Demonstrated ability to sit with non-technical business users, learn a messy manual process firsthand, and translate it into an automatable workflow without extensive requirements documentation.
• Autonomy: Comfortable operating with significant independence inside a division, making judgment calls on scope and design without constant central oversight.
• Education: Bachelor's degree or higher in Computer Science, Engineering, Financial Engineering, or a related quantitative field.

Required Technical Skills

• Core Engineering
• Strong proficiency in Java and/or Python for building and shipping production tools quickly.
• Strong SQL and data-modeling skills; comfort working against legacy enterprise data stores.
• Agentic AI & Rapid Prototyping
• Hands-on experience using agentic AI models and frameworks (tool-calling / function-calling, multi-step orchestration) to build working solutions quickly, rather than building agentic infrastructure from scratch.
• Retrieval-augmented generation for unstructured data (contracts, policy documents, correspondence, reports) common in control, risk, and compliance-adjacent workflows.
• Comfort working with vector databases and embedding pipelines at a practical, applied level (e.g., Milvus, Weaviate, Pinecone).
• Integration & Delivery
• Ability to integrate quickly with a division's existing systems, data stores, and internal APIs without lengthy platform build-out.
• Cloud deployment experience, ideally AWS.
• Comfort standing up lightweight monitoring for solution accuracy, usage, and reliability in a fast-moving embedded environment.
• Governance & Compliance
• Working knowledge of human-in-the-loop design patterns and audit-by-design logging suitable for a regulated decision-making environment.
• Enough fluency in model evaluation to flag when a workflow is not a good fit for automation, or needs additional guardrails.

Preferred / Differentiating Experience

• Prior experience as a Forward Deployed Engineer or in a similarly embedded delivery model at a technology company known for that approach is a strong plus.
• Prior work automating workflows in internal control, risk, compliance, financial reporting, or shared-services functions specifically, rather than only customer- or trading-facing systems.
• Experience using autonomous coding or task agents as part of a fast-moving delivery workflow.
• Exposure to financial industry regulatory standards and how they constrain automation design.
• Demonstrated comfort being the sole embedded technical resource within a business team, without a large supporting engineering team on-site.

What Success Looks Like (First 12 Months)

• Multiple workflows within the embedded function moved from manual process to working agentic automation in production, driven by direct collaboration with end users.
• A trusted, ongoing working relationship with divisional leadership, such that the FDE is proactively brought new automation opportunities rather than having to source them cold.
• Reusable components or patterns from the embedded work adopted by at least one other function or FDE.
• Clear, auditable documentation of deployed solutions sufficient to satisfy compliance and internal audit review.