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Forward Deployed AI Engineer

K-Tek Resourcing LLCNew York, NY🇺🇸United StatesPosted 13 Aug 2026

Why This Role Stands Out

This hybrid Forward Deployed AI Engineer role offers you the opportunity to drive impactful AI solutions from conception to deployment within a reputable firm, leveraging your engineering expertise and business acumen. You'll thrive here if you're a proactive problem-solver eager to own projects and deliver tangible results in a dynamic environment. Apply today to shape the future of AI in corporate functions!

Quick Overview

Work Type
Hybrid
Level
Mid Senior

Job Description

Role - Forward Deployed AI Engineer 

Location – NYC, NY

Mode: Hybrid

 

Role Overview

We are seeking a Forward Deployed AI Engineer to support Corporate, Compliance, Legal, and Risk Management functions across the firm. This is a hands-on delivery role: you will own the full arc of a solution — from requirements and design through build, testing, and production deployment — working directly with business and product teams to drive outcomes in a fast-paced, regulated environment.

 

The ideal candidate brings strong engineering fundamentals, deep practical experience with AI tools and workflows, and the maturity to operate effectively across technical and business audiences. You are comfortable taking ownership in ambiguous situations and are focused on shipping working solutions, not managing process.

 

 

The client  Platform – Mandatory skills

 

AI & Agents

Axon SDK · Azure AI Foundry · Azure OpenAI · Document Intelligence · AI Search · MCP broker

Orchestration

Temporal — agent runs, ETL pipelines, multi-step automations

Data

Snowflake via Delphi · Event Hubs · ADLS Gen2 · Cosmos DB · Redis · EDB Postgres

Cloud & Deployment

Azure · AKS · Flux GitOps · GitHub Actions · Terraform central module catalog

Observability

Datadog · Prometheus / Grafana · PagerDuty

ITSM & Identity

ServiceNow · Jira · Okta (OIDC) · Active Directory

 

Key Responsibilities

Delivery & Execution

       Lead end-to-end solution delivery across Corporate, Compliance, Legal, and Risk Management domains — from design and build through UAT and production deployment

       Own release readiness: manage UAT-to-production transitions, validate operational quality, and ensure solutions meet the firm''''s engineering and compliance standards

       Build and maintain CI/CD pipelines and DevOps processes on Apollo''''s Azure-based platform, working within established GitOps and Flux deployment patterns

       Manage delivery across multiple concurrent workstreams, coordinating with engineering, product, and business teams to maintain momentum and remove blockers

 

AI-Enabled Solution Design & Build

       Apply AI tools, agent frameworks, and workflow orchestration to solve business-critical problems — selecting the right approach and model for each use case rather than defaulting to the most complex solution

       Design and implement agent workflows on Apollo''''s Axon SDK and Azure AI Foundry, integrating Azure OpenAI, Document Intelligence, and AI Search

       Build multi-step automations and AI pipelines using Temporal as the firm''''s enterprise workflow orchestrator

       Integrate solutions with Apollo''''s data platform — consuming Snowflake data through the Delphi data PaaS, connecting to operational systems, and working within the firm''''s data governance model

       Expose and consume capabilities through Apollo''''s internal Model Context Protocol (MCP) broker pattern

 

Stakeholder Engagement

       Work directly with business leads, product managers, and domain teams to gather requirements, shape use cases, and translate them into clear, deliverable technical solutions

       Communicate progress, risks, and trade-offs clearly to both technical leads and senior business stakeholders

       Contribute to solution documentation, runbooks, and knowledge transfer as a standard part of delivery

 

Required Skills & Experience

Engineering & Delivery

       Proven track record of end-to-end solution delivery in production enterprise environments — design through deployment and ongoing operation

       Strong hands-on experience with Azure: AKS, Azure AI services, CI/CD pipeline implementation, and DevOps practices

       Solid understanding of GitOps deployment patterns and Flux-based release workflows

       Experience writing infrastructure configuration — Terraform or equivalent IaC — in a team-managed environment

       Comfortable working across the full delivery lifecycle including UAT coordination, operational readiness, and post-launch support

 

AI & Automation

       Deep practical experience with AI development workflows: agent design, prompt engineering, workflow orchestration, and model selection

       Hands-on experience with AI frameworks and orchestration tools — applied to real delivery problems, not proof-of-concept work

       Fluency with AI-assisted development tooling (Cursor, Claude, Codex) as a primary accelerant for engineering delivery

       Working knowledge of Azure AI Foundry, Azure OpenAI, Document Intelligence, and AI Search is strongly preferred

       Experience with Temporal or a comparable workflow orchestration platform is a plus

 

Domain & Environment

       Exposure to Corporate, Compliance, Legal, or Risk Management functions; understanding of the domain accelerates delivery significantly

       Strong communication and stakeholder management skills; ability to operate credibly at both working and senior levels

       Ownership mindset, high accountability, and the flexibility to meet delivery commitments in a demanding environment

 

Skills

ETL
Snowflake
Active Directory
Azure
Datadog
GitHub Actions
Grafana
Jira
PagerDuty
Prometheus
Redis
Stakeholder Management
Terraform

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