Software Engineer – Applied AI

DevRev

Forward Deployed Engineer developing AI-driven integrations and solutions at DevRev. Collaborating with customers to enhance their existing technologies and workflows through AI and automation.

Posted 4/27/2026full-timeRemote • 🇵🇭 PhilippinesMid-LevelSeniorWebsite

Tech Stack

Tools & technologies

AWSCloudGoGraphQLJavaScriptPythonSQLTypeScript

About the role

Key responsibilities & impact

Customer-facing: 30% working directly with customers.
Coding & Integration: 70-80% hands-on technical implementation
Build & Deploy Solutions: Design, develop, and launch AI agents, integrations, and automations that connect DevRev with customers' existing tech stacks and workflows.
Integrate Systems: Connect DevRev with SaaS and non-SaaS platforms through APIs, webhooks, and real-time communication architectures for seamless data flow.
Optimize AI Performance: Apply prompt engineering, fine-tune semantic search engines, and leverage generative AI techniques to enhance agent accuracy and user experience.
Own Data Insights: Write SQL queries, perform data analysis, and build dashboards to surface insights that drive customer decision-making.
Prototype & Iterate: Develop rapid proofs-of-concept, conduct live technical demos, and refine solutions based on customer and stakeholder feedback.
Lead Cross-functional Collaboration: Maintain constant communication loops with customers, engineering, product, customer success, support, and revenue teams to ensure alignment.
Guide Technical Adoption: Learn and master new tools, then guide customers through critical workflows like code repository integrations and advanced configurations.

Requirements

What you’ll need

Experience: 3+ years in software development, systems integration, or platform engineering. Customer-facing experience is a plus.
Background: Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field.
Coding Skills: Strong proficiency in TypeScript/JavaScript, Python, data structures and algorithms. (Nice to have: Go)
Applied AI Knowledge: Familiarity with large language models (LLMs), prompt engineering, frameworks like RAG and function calling, and building evals to validate agentic AI solutions.
Integration Expertise: Deep experience with large-scale data synchronization (one-way and two-way), API integration patterns (REST, GraphQL, webhooks), and event-driven/pub/sub architectures.
Cloud & Deployment: Hands-on experience deploying on serverless and edge platforms (AWS Lambda, Google Cloud Functions) with modern DevOps practices (CI/CD, containers, observability).
Data Transformation: Skilled in data mapping, schema alignment, and working with heterogeneous systems. Understanding of data modeling and graph data structures.
Observability: Experience implementing clear logging, actionable error surfacing, and telemetry to support faster debugging and issue resolution.
Context-Aware Systems: Familiarity with Model Context Programming (MCP) for building adaptive, context-aware integrations.
Problem-Solving: Strong track record triaging and unblocking both technical and non-technical blockers to keep projects moving forward.
Documentation: Experience writing concise, well-structured documentation that supports long-term team understanding and seamless onboarding.
Communication: Strong written and verbal skills to articulate technical concepts to engineers, product teams, and business stakeholders.

Benefits

Comp & perks

Travel Ready: Willingness to travel up to 30% for on-site implementations
Define the company-funded educational budget for personal and professional development
Encourage sharing knowledge and technical skills among team members to boost the overall company performance.

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

TypeScriptJavaScriptPythondata structuresalgorithmsprompt engineeringAPI integrationSQLdata analysiscloud deployment

Soft Skills

problem-solvingcommunicationcross-functional collaborationcustomer-facing experiencedocumentation

Certifications

Bachelor's degree in Computer ScienceMaster's degree in Engineering