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BS

Forward Deployed Engineer (FDE) – Agentic, Americas

Bestinfo Systems LLC
Posted 1 hour ago
📦Relocation support
🇺🇸United States
💰$200.0K–$250.0K📁
Engineering & Development
Is this job info correct?

Forward Deployed Engineer (FDE) – Agentic, Americas_Remote (Hartford, CT,Atlanta, GA,Daytona, FL,Houston, TX)_Full-Time(FTE)_Direct Hire


Position Title: Forward Deployed Engineer (FDE) – Agentic, Americas

Job Type: Full-Time

Base Salary: $200,000 to $250,000 + Best-in-class benefits

Location: Remote (Hartford, CT,Atlanta, GA,Daytona, FL,Houston, TX)

Willing to relocate to one or more of the following locations?

* Hartford, CT

* Atlanta, GA

* Daytona, FL

* Houston, TX


Job Description:

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 on 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 the company 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 LTM focus verticals (Travel/Transportation/Hospitality, Retail/CPG, BFSI, Manufacturing, Media).

* Relevant certifications (cloud, security, data) are a plus.


Compensation:

*Full-time

*Benefits - Full

*Relocation Assistance Available - Possible for ideal candidate


Candidate Details:

*7+ to 10 years experience

*Seniority Level - Director

*Minimum Education - Bachelor's Degree

*Willingness to Travel - Occasionally


Ideal Candidate:


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.

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