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Forward Deployed Engineer
Forward Deployed Engineer
Overview
Application
Location
Flexible — Remote / US / India
Employment Type
Full-Time
Department
Field Engineering
Experience
Senior (5+ years)
Type
Full-Time
About Rive
Rive is building the Agentic Operating System for Industrial Assets — a platform where asset data, processes, and AI agents work together to orchestrate maintenance, reliability, and supply-chain decisions automatically.
We unify fragmented industrial data into a configurable ontology and knowledge graph, and empower customers with autonomous AI agents that continuously enrich data quality, improve reliability, and drive operational outcomes. We are currently in stealth mode, backed by strong early customer traction across manufacturing, fleet, utilities, and heavy industries.
Role Overview
As a Forward Deployed Engineer (FDE), you are the technical force that turns Rive’s platform into measurable outcomes inside our customers’ environments. You sit at the front line — embedding with customers to understand their assets, data, and operational pain, then designing, building, and deploying the integrations, configurations, and agent workflows that make Rive work for them.
You will move fluidly between writing production code, integrating with complex enterprise systems, tuning Rive’s AI agents and ontology to customer data, and translating ambiguous business requirements into shipped solutions. This is a high-ownership, customer-facing engineering role for someone who loves being in the field, solving real problems end-to-end, and carrying a deployment from first conversation to production value.
What You’ll Do
Customer Deployment & Onboarding
Embed with enterprise customers to scope, design, and lead end-to-end deployments of the Rive platform.
Own customer onboarding — ingest and map their asset data, configure the ontology and knowledge graph, and stand up a working system in their environment.
Build and operate integrations to customer systems of record such as SAP PM, IBM Maximo, Infor, and Hexagon, as well as data lakes, historians, and document repositories.
Requirements Understanding & Solutioning
Work directly with customer stakeholders — reliability engineers, maintenance teams, supply-chain and IT — to understand their workflows and translate ambiguous business needs into concrete technical solutions.
Run technical discovery and scoping; design solution architectures and clearly communicate trade-offs to both customers and the internal product team.
Act as the voice of the customer back to engineering, shaping the roadmap with real field insight.
AI & Agent Tuning
Configure and tune Rive’s autonomous agents — data quality, asset enrichment, spare-parts deduplication, and decision/workflow agents — to each customer’s data and domain.
Build and refine retrieval, embedding, and prompt strategies so agents reason accurately over customer-specific assets, parts, documents, and failure histories.
Evaluate agent output with customers, set up feedback loops, and continuously improve accuracy, reliability, and trust.
Full-Stack Build
Design and implement APIs, services, and data pipelines that support complex enterprise workflows.
Build responsive, customer-facing interfaces and internal tooling to accelerate deployments and surface insights.
Deploy and operate applications on hyperscale cloud platforms (AWS, GCP, Azure), ensuring security, performance, reliability, and scalability.
Support production systems, troubleshoot live issues, and drive continuous improvement across accounts.
Required Qualifications
5+ years building and deploying production software, with meaningful time spent working directly with customers or enterprise stakeholders.
Strong full-stack engineering skills — a backend language such as Python or Java/Spring Boot, plus a modern frontend framework like React (or Angular, Vue, or equivalent).
Hands-on experience with at least one hyperscaler (AWS, GCP, or Azure) and a solid grasp of RESTful APIs, microservices, and distributed systems.
Proven experience integrating with large enterprise systems (e.g., SAP, IBM, Hexagon, Maximo, or similar).
Working knowledge of applied AI — LLMs, embeddings, RAG, or agent frameworks — and comfort tuning them for real-world data.
Experience with relational and/or NoSQL databases, CI/CD pipelines, and DevOps practices.
Excellent communication skills and the ability to lead technical conversations with customers and translate requirements into solutions.
Willingness to travel to customer sites as needed.
Preferred Qualifications
Experience with industrial data, asset management, or maintenance systems (SAP PM, Maximo, Infor, Hexagon).
Experience deploying ML/AI systems in production (Docker, Kubernetes, MLflow, SageMaker, Vertex AI, or similar).
Background in entity matching, ontology-based reasoning, NLP, document intelligence, or knowledge graphs (Neo4j, Neptune, TigerGraph).
Prior experience as a forward deployed, solutions, or applications engineer at an enterprise or early-stage software company.
Exposure to event-driven architectures, messaging systems, and multi-cloud or hybrid-cloud environments.
Who You Are
A first-principles thinker who thrives in ambiguity and is energized by being in front of customers.
A strong owner who can take a problem from idea → prototype → production with minimal hand-holding.
Pragmatic and delivery-oriented, balancing speed with quality under real-world constraints.
Low-ego, collaborative, and genuinely curious about how factories, fleets, and infrastructure actually run.
What You’ll Get
Shape how a category-defining product gets deployed and adopted in the real world.
Direct access to real industrial data and customers from day one, with strong influence on product direction.
Work alongside a global founding team (ex-SAP, industrial, and AI systems experts).
Competitive equity and compensation package.
The chance to drive impact across manufacturing, logistics, energy, and fleet operations at global scale.
Apply for this Job
Overview
Application
Location
Flexible — Remote / US / India
Employment Type
Full-Time
Department
Field Engineering
Experience
Senior (5+ years)
Type
Full-Time
About Rive
Rive is building the Agentic Operating System for Industrial Assets — a platform where asset data, processes, and AI agents work together to orchestrate maintenance, reliability, and supply-chain decisions automatically.
We unify fragmented industrial data into a configurable ontology and knowledge graph, and empower customers with autonomous AI agents that continuously enrich data quality, improve reliability, and drive operational outcomes. We are currently in stealth mode, backed by strong early customer traction across manufacturing, fleet, utilities, and heavy industries.
Role Overview
As a Forward Deployed Engineer (FDE), you are the technical force that turns Rive’s platform into measurable outcomes inside our customers’ environments. You sit at the front line — embedding with customers to understand their assets, data, and operational pain, then designing, building, and deploying the integrations, configurations, and agent workflows that make Rive work for them.
You will move fluidly between writing production code, integrating with complex enterprise systems, tuning Rive’s AI agents and ontology to customer data, and translating ambiguous business requirements into shipped solutions. This is a high-ownership, customer-facing engineering role for someone who loves being in the field, solving real problems end-to-end, and carrying a deployment from first conversation to production value.
What You’ll Do
Customer Deployment & Onboarding
Embed with enterprise customers to scope, design, and lead end-to-end deployments of the Rive platform.
Own customer onboarding — ingest and map their asset data, configure the ontology and knowledge graph, and stand up a working system in their environment.
Build and operate integrations to customer systems of record such as SAP PM, IBM Maximo, Infor, and Hexagon, as well as data lakes, historians, and document repositories.
Requirements Understanding & Solutioning
Work directly with customer stakeholders — reliability engineers, maintenance teams, supply-chain and IT — to understand their workflows and translate ambiguous business needs into concrete technical solutions.
Run technical discovery and scoping; design solution architectures and clearly communicate trade-offs to both customers and the internal product team.
Act as the voice of the customer back to engineering, shaping the roadmap with real field insight.
AI & Agent Tuning
Configure and tune Rive’s autonomous agents — data quality, asset enrichment, spare-parts deduplication, and decision/workflow agents — to each customer’s data and domain.
Build and refine retrieval, embedding, and prompt strategies so agents reason accurately over customer-specific assets, parts, documents, and failure histories.
Evaluate agent output with customers, set up feedback loops, and continuously improve accuracy, reliability, and trust.
Full-Stack Build
Design and implement APIs, services, and data pipelines that support complex enterprise workflows.
Build responsive, customer-facing interfaces and internal tooling to accelerate deployments and surface insights.
Deploy and operate applications on hyperscale cloud platforms (AWS, GCP, Azure), ensuring security, performance, reliability, and scalability.
Support production systems, troubleshoot live issues, and drive continuous improvement across accounts.
Required Qualifications
5+ years building and deploying production software, with meaningful time spent working directly with customers or enterprise stakeholders.
Strong full-stack engineering skills — a backend language such as Python or Java/Spring Boot, plus a modern frontend framework like React (or Angular, Vue, or equivalent).
Hands-on experience with at least one hyperscaler (AWS, GCP, or Azure) and a solid grasp of RESTful APIs, microservices, and distributed systems.
Proven experience integrating with large enterprise systems (e.g., SAP, IBM, Hexagon, Maximo, or similar).
Working knowledge of applied AI — LLMs, embeddings, RAG, or agent frameworks — and comfort tuning them for real-world data.
Experience with relational and/or NoSQL databases, CI/CD pipelines, and DevOps practices.
Excellent communication skills and the ability to lead technical conversations with customers and translate requirements into solutions.
Willingness to travel to customer sites as needed.
Preferred Qualifications
Experience with industrial data, asset management, or maintenance systems (SAP PM, Maximo, Infor, Hexagon).
Experience deploying ML/AI systems in production (Docker, Kubernetes, MLflow, SageMaker, Vertex AI, or similar).
Background in entity matching, ontology-based reasoning, NLP, document intelligence, or knowledge graphs (Neo4j, Neptune, TigerGraph).
Prior experience as a forward deployed, solutions, or applications engineer at an enterprise or early-stage software company.
Exposure to event-driven architectures, messaging systems, and multi-cloud or hybrid-cloud environments.
Who You Are
A first-principles thinker who thrives in ambiguity and is energized by being in front of customers.
A strong owner who can take a problem from idea → prototype → production with minimal hand-holding.
Pragmatic and delivery-oriented, balancing speed with quality under real-world constraints.
Low-ego, collaborative, and genuinely curious about how factories, fleets, and infrastructure actually run.
What You’ll Get
Shape how a category-defining product gets deployed and adopted in the real world.
Direct access to real industrial data and customers from day one, with strong influence on product direction.
Work alongside a global founding team (ex-SAP, industrial, and AI systems experts).
Competitive equity and compensation package.
The chance to drive impact across manufacturing, logistics, energy, and fleet operations at global scale.
Apply for this Job
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©2026 Rive. All rights reserved.
©2026 Rive. All rights reserved.