Forward Deployed Engineer (FDE) – Agentic AI, Americas 

Role Type: Client-facing, hands-on engineering + solutioning (pre-sales through early delivery)
Location: Major US hub (e.g., New York, Bay Area, Dallas, Chicago – flexible for the right candidate).
Hybrid arrangements and travel: This remain hybrid opportunities in New York, the Bay Area, Dallas, or Chicago, with no fully remote option. Travel may be approximately 25%, when necessary.
Level: Manager/Principal/Senior Principal
Business Unit: Enterprise AI Platforms & Agentic Solutions
Reporting to: Artificial Intelligence Leader, North America

Company Overview:
Global technology consulting and digital solutions company that enables enterprises across industries to reimagine how they operate, compete, and grow. By combining deep domain knowledge, advanced engineering, and transformation expertise, delivers measurable business impact at scale.

Enterprise AI business unit, purpose built to help organizations move beyond pilots into scaled, product iongrade AI adoption, functional consulting, an AI Foundry, and agentic AI platforms to deliver integrated solutions that transform how work gets done across the enterprise.Operating across Banking, Insurance, Manufacturing, Retail/CPG, Energy & Utilities, Travel & Hospitality, HiTech, and Media,  works closely with industry GTM teams to create repeatable AI solutions, accelerators, and transformation programs aligned to real business outcomes.

Role summary

Building and scaling enterprise grade GenAI + Agentic AI capabilities (Foundry, orchestration, governance/AgentOp, accelerators, and verticalized agents) across Fortune 2000 clients. 

As a Forward Deployed Engineer (FDE), you will operate at the intersection of executive problem framing, rapid engineering, and scalable architecture. You will engage directly with client CXOs and ssseni or leaders to identify a highvalue wedge, build a working proof in weeks, and translate that into a clear path toward MVP and scaled rollout on  or nay hyper-scaler platforms. 

You will be embedded in deals and client journeys—shipping real agentic systems, not slides. 

Key Responsibilities 

1) Executive-facing discovery & value shaping 

Partner with Sales, Client Partners, and  leaders to run CXO-level working sessions that translate business pain into an Outcome Thesis (KPI tree, baseline, uplift hypothesis, operating constraints). 
Identify the right “thin-slice” wedge for a rapid Proof of Value (PoV): high signal, measurable, low dependency, enterprise-relevant. 
Communicate trade-offs clearly: what to automate vs assist, where human-in-the-loop is required, and what “safe scale” entails.

2) Rapid Proof of Value engineering  

Build a rapid PoV that demonstrates business impact + technical feasibility trustworthiness
Implement agent workflowswith tooluse, integration to enterprise systems, and lightweight UI/experience for stakeholder clarity. 
Create initial evaluation harness (task success, accuracy, policy compliance, tool-call success, latency/cost) and capture baseline vs PoV lift.

3) Agentic blueprint & path-to-scale handoff 

Produce a scalable Agentic Blueprint: agent roles, orchestration patterns, tools/APIs, data/knowledge strategy, guardrails, observability, and HIL escalation. 
Define MVP backlog and architecture decisions: identity/access, audit, logging, fallback design, policy boundaries, and deployment model. 
Hand off cleanly to delivery teams (MVP squads / pods) with a production-ready plan.

4) Solution architecture + client ecosystem 

Design solutions using  constructs or hyper scaler Agentic AI foundations (Foundry, knowledge fabric/RAG patterns, agent orchestration, governance, observability/AgentOps
Deploy across hyperscalers (AWS/Azure/GCP) and/or client environments; integrate with enterprise apps (e.g., ServiceNow, Salesforce, SAP, Microsoft stack). 
Ensure alignment with enterprise security, privacy, and compliance requirements.

5) Deal acceleration & differentiation 

Serve as a technical “closer” in competitive pursuits: demos, workshops, architecture deep dives, and technical validation. 
Create reusable accelerators: prompt packs, workflow templates, connectors, eval suites, reference architectures—so future PoVs become faster and repeatable. 
Contribute to  thought leadership and field playbooks (industry use cases, POV patterns, autonomy ladder constructs, commercial hooks).

What success looks like (12-month outcomes) 

Time-to-first-value: PoVs that reliably land in weeks with measurable outcomes. 
Conversion: Strong PoV to MVP conversion rate (and clear roadmap to scale). 
Executive confidence: CXO trust built through crisp narratives + working systems. 
Reusable assets: Field-ready accelerators that reduce PoV cycle time quarter over quarter. 
Scalability: PoVs designed with production realities in mind (security, observability, cost, controls).

Required Qualifications 

8+ years of experience in full-stack engineering / solution architecture / technical consulting, with significant client-facing delivery. 
Demonstrated ability to build quickly under ambiguity and still maintain sound architecture instincts. 
Strong experience with modern AI stacks, including: 
LLMs / agent patterns: orchestration, tool-calling, planning/execution loops, memory patterns 
RAG & knowledge: embedding strategies, chunking, vector databases, retrieval evaluation 
Evaluation: offline + online evals, regression suites, safety tests/red-teaming basics 
Strong software engineering fundamentals: APIs, data pipelines, integration, distributed systems basics.
Proficiency in Python + one of (TypeScript/Java/Go); comfortable across frontend + backend as needed.
Cloud-native experience (AWS/Azure/GCP), containers, CI/CD, and observability fundamentals. 
Exceptional communication: can translate technical complexity into business impact for senior stakeholders.

Preferred Qualifications 

Proven delivery of GenAI/agentic solutions in production (not only prototypes). 
Experience integrating with enterprise platforms: ServiceNow, Salesforce, SAP, Microsoft (Graph/O365), Databricks/Snowflake, etc. 
Experience with security & governance for GenAI: data boundaries, access control, auditability, model risk, compliance evidence. 
Familiarity with LLMOps/AgentOps concepts: versioning, telemetry, drift monitoring, cost governance (FinOps). 
Domain depth in one or more focus verticals (Travel/Transportation/Hospitality, Retail/CPG, BFSI, Manufacturing, Media). 
Relevant certifications (cloud, security, data) are a plus.

Core competencies (what distinguishes top performers) 

Executive presence: credible with CXOs; can run a room and drive decisions. 
Structured problem framing: quickly identifies the highest-leverage wedge and measurement plan. 
Builder mindset: ships working systems rapidly; demos are grounded in real integrations. 
Judgment & trust: knows where agents must be constrained; designs for safe autonomy. 
Repeatability: turns one-off wins into reusable playbooks and accelerators.

Working model 

Travel: expected (client workshops, PoVs, exec meetings). 
Operates in tight pods with Sales, Industry leaders, BlueVerse product/platform teams, and delivery squads. 
Strong bias toward hands-on building (this role is not purely advisory).

Benefits

Comprehensive Medical Plan Covering Medical, Dental, Vision
Short Term and Long-Term Disability Coverage
401(k) Plan with Company match
Life Insurance
Vacation Time, Sick Leave, Paid Holidays
Paid Paternity and Maternity Leave

Forward Deployed Engineer (FDE) – Agen...

 Forward Deployed Engineer (FDE) – Agen...