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AI Engineer

InvestM Technology LLCUnited States🇺🇸United StatesPosted 17 Aug 2026

Quick Overview

Work Type
Hybrid
Level
Mid Senior

Job Description

Senior Forward Deployed Engineer – Agentic AI / LLM / RAG
Contract
Remote
 
Must Haves:
Multi-agent orchestration, LLM, RAG workflows, SLM fine-tuning, Python, Docker, Kubernetes, CI/CD, GraphQL
 
Job Description: 
A fast-growing enterprise AI company is looking for a Senior Forward Deployed Engineer to take technical ownership of strategic AI solution deployments for enterprise customers. This role combines hands-on engineering, solution architecture, customer partnership, and delivery leadership, with a focus on building customer-specific applications on an Agentic AI platform.
 
You will lead the architecture, prototyping, implementation, and post-deployment optimization of large-scale Agentic and Knowledge AI solutions. The role involves working across enterprise data pipelines, multi-agent orchestration, RAG workflows, SLM fine-tuning, platform customization, full-stack delivery, and production-grade AI systems. You will collaborate closely with customers, Product, Platform Engineering, and cross-functional teams to translate ambiguous business needs into scalable engineering plans and successful deployments.
 
 
Requirements
Required Skills
  • 10+ years of engineering experience, including at least 2 years in customer-facing, field engineering, solutions engineering, or forward deployed engineering roles
  • Proven experience building and deploying AI/ML, data-intensive, or enterprise-grade applications in production
  • Strong full-stack development experience with Python, Node.js or Go, and React or Vue
  • DevOps experience with Docker, Kubernetes, CI/CD, and modern cloud-based deployment practices
  • Experience designing and implementing enterprise data pipelines and system integrations
  • Strong knowledge of REST APIs, Python, SQL, GraphQL, Webhooks, and enterprise integration patterns
  • Solid understanding of LLMs, prompt engineering, prompt tuning, vector databases, RAG pipelines, and agentic workflows
  • Experience with vector databases such as AstraDB, Pinecone, or Weaviate
  • Familiarity with RAG frameworks such as LlamaIndex or Haystack
  • Experience with agent and workflow orchestration tools such as LangChain, LangGraph, or CrewAI
  • Ability to lead technical solution design and implementation for strategic enterprise customers
  • Experience customizing platform components, integrating APIs, building reusable tooling, or extending platform logic
  • Strong understanding of observability, monitoring, versioning, telemetry, and trustworthy AI deployment practices
  • Ability to translate ambiguous customer needs into clear, actionable engineering plans
  • Strong project ownership, mentoring, communication, and collaboration skills across technical and business stakeholders
  • Undergraduate degree, master’s degree, or PhD in Computer Science, Data Science, or a related technical field.
Bonus Skills
  • Knowledge of SLM fine-tuning, model distillation, and model optimization techniques
  • Experience building and delivering enterprise Agentic AI solutions
  • Experience working with Agentic development platforms
  • Familiarity with graph databases, multimodal AI systems, evaluation frameworks, security, guardrails, and GPU infrastructure trends
  • Experience contributing to reusable assets, technical best practices, internal frameworks, and documentation
  • Prior experience supporting post-deployment optimization and production adoption for enterprise customers
  • Experience partnering with Product and Platform Engineering teams to identify feature gaps, customer pain points, and product improvement opportunities.

Skills

Docker
Node.js
SQL
GraphQL
Kubernetes
LLM
Python
REST
React
Vue

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