What does a Forward Deployed Engineer do at Realign?

Forward Deployed Engineers at Realign are embedded directly with enterprise customers to implement and customize the platform, build integrations, and solve technical problems in real-world client environments. They combine software engineering skills with direct customer interaction, writing production code while also serving as the primary technical point of contact.

What skills are required for this Senior Forward Deployed GenAI Engineer role?

The Senior Forward Deployed GenAI Engineer role at Realign typically requires strong software engineering skills (Python, TypeScript, SQL), experience with APIs and system integration, comfort with cloud platforms, and the ability to communicate complex technical topics to non-technical stakeholders. Most FDE roles require 3-7 years of engineering experience.

Is this Forward Deployed Engineer position at Realign remote?

Remote availability varies by Realign FDE role. Some positions are fully remote, others require travel to customer sites, and some are hybrid. Check the full job description above for the specific location requirements for this posting.

Realign

Senior Forward Deployed GenAI Engineer

Remote TX, US Senior Posted October 06, 2026

Apply on Indeed All FDE Jobs

Role Description

Remote, Texas 75001 Posted October 7th, 2026

Job Type: Contract

Job Category: IT

Job Description

Role – Senior Forward Deployed GenAI Engineer

Location – Remote

Contract

Forward Deployed Engineer (FDE) – GenAI and help enterprise customers transform AI concepts into production-ready, business-critical applications.

Key Responsibilities

Design, develop, and deploy production-grade GenAI and Agentic AI solutions.

Build and optimize: Multi-Agent Systems, MCP Servers, RAG-Based Applications, Enterprise AI Pipelines, Evaluation & Observability Frameworks

Integrate Google AI technologies with enterprise ecosystems, APIs, legacy systems, and data platforms.

Develop scalable AI architectures focused on performance, accuracy, security, and latency optimization.

Partner directly with customer engineering teams to deliver impactful AI solutions and drive adoption.

Required Skills

5+ years of software development experience using Python or similar programming languages

Strong hands-on experience with: Google Cloud Platform (GCP), Generative AI & Agentic AI, Vector Databases, RAG Architectures, Enterprise AI Deployments, Full-Stack Development

Experience building structured and unstructured data pipelines and taking AI solutions from concept to production.

Hands-on experience with: Gemini-powered Conversational AI, Customer Engagement Suite (CES), Contact Center AI (CCAI)

Experience leading technical discovery sessions and customer-facing engagements.

Preferred Qualifications

Master's or PhD in Computer Science, AI, or related field

Experience with: LangGraph, CrewAI, Agent Development Kit (ADK), ReAct Framework, Self-Reflection Agents, Multi-Agent Architectures

Strong understanding of: LLM Performance Metrics, State Management, Observability & Tracing, AI Cost Optimization

Required Skills

DevOps Engineer

About Forward Deployed Engineering

Forward Deployed Engineers are embedded directly with customers to build custom solutions, integrate products into existing infrastructure, and bridge the gap between product engineering and customer success. The role combines deep technical skills with the ability to operate in client environments and translate business requirements into working software.

Originally pioneered by Palantir, the FDE model has spread across AI, enterprise SaaS, and cloud infrastructure companies. FDEs write production code, architect integrations, train customer teams, and feed product insights back to the core engineering organization. At companies like OpenAI, Salesforce, and Databricks, FDE teams are treated as elite engineering units that can ship custom solutions in days rather than quarters.

Typical FDE stack: Python, TypeScript, SQL, REST/GraphQL APIs, cloud platforms (AWS/GCP/Azure), and increasingly LLM APIs and AI orchestration frameworks. Strong communication and the ability to context-switch between technical and business conversations are as important as coding ability.