Note: The job is a remote job and is open to candidates in USA. Reqroute, Inc is seeking a Senior Forward Deployed Software Engineer to support ServiceNow’s Applied AI Forward Deployed Engineering team. The role focuses on building, deploying, and scaling secure LLM-enabled applications, collaborating closely with customers, and creating reusable engineering assets and platform improvements.
Responsibilities
- Build solution-ready LLM-enabled applications that span backend logic, data orchestration, and front-end UI
- Operate in the field, working side-by-side with customers to adapt, deploy, and iterate in live environments
- Codify reusable assets—libraries, prompts, scaffolds—to accelerate future engagements
- Shape developer experience by sharing feedback with platform and product teams
- Deliver Production - readysolution in agile end-to-end sprints
- Engineer with versatility: APIs, orchestration pipelines, vector DBs, LLM frameworks, UI components
- Operate with agility: integrate with legacy systems, navigate ambiguity, ship safely at speed
- Codify patterns: build scaffolds, SDKs, and documentation to scale success across customers
- Influence platform: inform product strategy through field-tested insights and extensible code
Skills
- Experience: In leveraging or critically thinking about how to integrate AI into work processes, decision-making, or problem-solving. This may include using AI-powered tools, automating workflows, analyzing AI-driven insights, or exploring AI's potential impact on the function or industry
- Relevant Experience: 8+ years of software engineering, including 2+ years building systems in customer-facing or embedded roles
- System architecture: Proven ability to design and implement AI-native software in production environments
- Engineering depth: Strength in backend (Python, Node.js, Java), frontend (React, Angular), APIs (REST/GraphQL)
- LLM tooling: Familiarity with LangChain, Semantic Kernel, prompt chaining, vector search, and context management
- Performance & observability: Skilled in debugging distributed systems, tuning for latency, and implementing monitoring
- Platform mindset: Can contribute to shared SDKs and tools, raising engineering velocity for the whole org
- Product sensibility: Prioritize for user value, MVP iteration, and long-term scale
- DevOps fluency: Experience deploying in AWS, Azure, or GCP with CI/CD, containers, and infra-as-code
- Field readiness: Able to travel up to 30% to embed onsite and deliver where it matters
Benefits
- Remote work arrangement
Company Overview