Forward Deployed Engineer (FDE) – AI/GenAI & Telecom
Role Description
Forward Deployed Engineer (FDE) – AI/GenAI & Telecom
Location : Stamford, CT
Years of Exp: 10–15+ years of software/data/AI engineering experience ,
Role Summary
We are looking for a hands-on Forward Deployed Engineer who can work closely with Spectrum business, product, operations, and engineering teams to identify high-value problems and rapidly design, prototype, deploy, and productionize AI/GenAI solutions.
The ideal candidate combines strong software engineering skills with Generative AI, agentic AI, data engineering, cloud, APIs, and telecom/broadband domain knowledge . The role requires someone comfortable working directly with customer stakeholders and taking solutions from an ambiguous business problem through production deployment.
Key Responsibilities
- Work directly with Spectrum stakeholders to understand business and engineering problems and translate them into deployable technical solutions.
- Rapidly prototype and productionize GenAI/LLM and agentic AI applications .
- Build RAG-based applications , AI assistants, semantic search, and enterprise knowledge solutions.
- Develop agentic workflows using frameworks such as LangChain/LangGraph and integrate agents with enterprise applications and APIs.
- Build backend services and integrations using Python, REST APIs, GraphQL, FastAPI, SQL and microservices .
- Integrate AI solutions with telecom platforms, including OSS/BSS, CRM, field-service, network/service operations and enterprise knowledge systems .
- Work with structured and unstructured data, embeddings, vector databases and enterprise data sources.
- Implement AI evaluation, observability, guardrails, groundedness checks and hallucination mitigation.
- Deploy containerized applications using Docker/Kubernetes and cloud platforms such as AWS, Azure or GCP.
- Troubleshoot customer-environment issues and optimize solutions for reliability, scalability, latency and production readiness.
- Partner with product and engineering teams and provide feedback from customer deployments to improve reusable solutions.
These areas line up strongly with the FDE-oriented candidate material already being shared with Spectrum, including telecom/broadband operations, GenAI, RAG, LangChain/LangGraph, API integration, vector databases, AI observability and cloud-native deployment.
Required Skills
- Strong hands-on programming in Python
- GenAI / LLM application development
- RAG, embeddings, vector databases and semantic search
- Agentic AI / agent orchestration
- LangChain and/or LangGraph
- REST APIs, FastAPI, GraphQL and microservices
- SQL and data integration
- AWS, Azure or GCP
- Docker and Kubernetes
- CI/CD and software engineering best practices
- Strong debugging and production troubleshooting skills
- Excellent customer-facing communication and ability to work with ambiguous requirements
Preferred Telecom Experience
- Cable/Broadband/Telecom domain
- OSS/BSS platforms
- Network/service operations
- Field-service applications and workflows
- CRM/customer-care platforms
- Network and operational data
- AI-powered troubleshooting and knowledge assistants
Years of Exp: 10–15+ years of software/data/AI engineering experience , with recent hands-on experience building production GenAI solutions. The person should be a builder first , comfortable sitting with the customer, understanding the problem, coding a prototype quickly, and then taking it into production.
In summary , “Hands-on customer-facing AI engineer who can understand Spectrum’s business/telecom problem, rapidly build a GenAI/Agentic AI solution, integrate it with existing systems, and take it through production.”
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.
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