Engineering

Forward Deployed Engineer

Invovia IncFrisco, TX🇺🇸United StatesPosted Oct 14, 2026

Why This Role Stands Out

This Forward Deployed Engineer role offers a unique opportunity to drive impactful AI solutions for enterprise clients, fostering significant growth in your technical and client-facing skills. You'll thrive here if you're an experienced engineer passionate about building and deploying cutting-edge AI applications, enjoying a hybrid work model that balances collaboration with flexibility. Apply today to shape the future of AI with Invovia Inc!

Quick Overview

Seniority

Mid Senior

Work mode

Hybrid

Location

Frisco, TX, United States

Posted

19 hours ago

Job Description

About the Role

We are looking for an experienced Forward Deployed Engineer (FDE) to work at the intersection of AI, software engineering, and customer success. In this role, you will partner closely with enterprise customers to understand their business challenges and design, build, and deploy production-grade AI solutions that deliver measurable business outcomes.

As a Forward Deployed Engineer, you will embed with customer teams, rapidly prototype solutions, and take them to production using modern AI technologies, cloud platforms, and enterprise integrations. You will own the complete delivery lifecycle—from problem discovery through deployment, adoption, and continuous optimization.

Key Responsibilities

Customer Engagement & Solution Design

Partner closely with internal teams and enterprise customers to understand business workflows, operational challenges, and strategic objectives.
Translate customer requirements into scalable AI-powered software solutions that deliver measurable business value.
Serve as the primary technical advisor throughout solution delivery, building trusted relationships with customer stakeholders.

AI Solution Development

Design, develop, and deploy production-grade agentic AI applications, including voice agents, chat agents, AI copilots, and workflow automation solutions.
Build Retrieval-Augmented Generation (RAG) pipelines, prompt orchestration frameworks, and multi-agent systems tailored to customer-specific use cases.
Develop robust prompt engineering strategies and evaluation frameworks to ensure accuracy, reliability, and performance of AI systems.
Rapidly prototype proof-of-concepts, incorporate customer feedback, and transition successful solutions into production on an iterative delivery cycle.

Enterprise Integration

Integrate AI applications with enterprise data sources, APIs, third-party platforms, and business applications.
Build and maintain scalable data ingestion pipelines to prepare structured and unstructured data for AI workloads.
Navigate complex enterprise environments involving heterogeneous systems and legacy integrations.

Production Ownership

Own the complete deployment lifecycle, including implementation, monitoring, optimization, and ongoing support.
Continuously improve solution reliability, scalability, latency, and user adoption after deployment.
Troubleshoot production issues and implement long-term improvements to enhance customer success.

Collaboration & Leadership

Partner with Product and Engineering teams to communicate recurring customer challenges and influence product roadmap decisions.
Establish engineering best practices, reusable frameworks, deployment playbooks, and operational standards for the Forward Deployed Engineering function.
Mentor junior engineers and contribute to building a high-performing engineering culture.

Required Qualifications

Experience

8+ years of professional software engineering experience building and deploying production applications.
Proven experience owning complex technical projects from concept through production with minimal supervision.
Demonstrated success working directly with enterprise customers in solution delivery or consulting-oriented engineering roles.

Software Engineering

Expert-level proficiency in Python.
Strong programming skills in at least one additional language such as JavaScript/TypeScript, Java, or Go.
Deep understanding of software architecture, distributed systems, REST APIs, and full-stack application development.

Generative AI Engineering

Hands-on experience deploying LLM-powered applications into production environments.
Strong expertise in:

Prompt Engineering
Retrieval-Augmented Generation (RAG)
Agentic AI architectures
Multi-agent orchestration
AI evaluation and optimization

Experience with frameworks such as LangChain, LlamaIndex, or equivalent orchestration platforms.

Data Engineering

Strong SQL skills with experience designing and optimizing complex queries.
Experience building ETL/ELT pipelines and working with enterprise data platforms.
Hands-on experience with modern data warehouses such as Snowflake, Databricks, or equivalent platforms.
Ability to transform and prepare enterprise datasets for AI applications.

Cloud & DevOps

Experience deploying applications on AWS, Azure, or Google Cloud Platform.
Hands-on experience with Docker containers, CI/CD pipelines, infrastructure automation, and production deployments.
Familiarity with cloud-native architectures and scalable application deployment practices.

Customer Engagement

Strong customer-facing experience delivering enterprise software solutions.
Ability to navigate ambiguous environments, gather requirements, conduct technical workshops, and communicate effectively with technical teams and executive stakeholders.
Excellent written and verbal communication skills.

Leadership

Experience leading technical initiatives and influencing engineering decisions.
Ability to mentor engineers and establish engineering best practices.
Strong ownership mindset with a bias toward execution, continuous learning, and rapid iteration.

Preferred Qualifications

Experience with MLOps practices, including model versioning, experimentation frameworks, monitoring, and observability.
Experience with vector databases such as Pinecone, Milvus, pgvector, or equivalent technologies.
Experience deploying AI solutions across enterprise domains such as customer support, retail, finance, supply chain, or manufacturing.
Strong understanding of enterprise data ecosystems and governance.
Experience building new engineering functions or working as an early member of a high-growth engineering team.

What Makes You Successful

You thrive in ambiguous, fast-paced environments.
You enjoy solving difficult customer problems with practical engineering solutions.
You balance rapid experimentation with production-quality engineering.
You are equally comfortable discussing system architecture with engineers and business outcomes with executives.
You take ownership of customer outcomes, not just software delivery.