Forward Deployed Engineer (AI/GenAI)

CHI Software is a global software development services provider delivering AI-driven solutions, cloud services and data engineering across EdTech, FinTech, HealthTech. We help businesses modernize, scale, and unlock new value through the latest technologies.
We are looking for Forward Deployed Engineer (AI/GenAI)

As a Forward Deployed Engineer, you will work directly with enterprise customers to design, build, deploy, continuously improve AI-powered solutions that solve real business challenges.

This is an engineering role with end-to-end ownership. You’ll partner with customers to understand their business processes, data, technology landscape, identify where AI can create measurable value, architect production-ready solutions, lead their implementation from discovery through deployment and continuous optimization.

You’ll combine software engineering, AI engineering, solution architecture, and customer consulting in a single role.

Success is measured by production adoption, customer outcomes, business impact, not by the number of completed tickets.

Customer Engagement & Solution Delivery

• Own AI solution delivery from technical discovery through production deployment and continuous improvement.
• Analyze customer business processes, engineering workflows, enterprise systems, and data landscape to identify high-impact AI opportunities.
• Help customers improve both business operations and software delivery (SDLC) through AI adoption where appropriate.
• Translate business challenges into scalable, production-ready AI solution architectures.
• Prototype rapidly, validate with business users and technical stakeholders, and iterate based on measurable outcomes.
• Present architectural decisions, trade-offs, implementation strategies, and technical risks to both technical and business audiences.
• Capture implementation learnings and transform them into reusable delivery patterns, accelerators, and best practices.

AI Engineering & Architecture

• Design, build, or extend enterprise applications with AI capabilities using the technology stack that best fits each customer’s environment.
• Develop production-grade AI solutions using LLMs, AI agents, Retrieval-Augmented Generation (RAG), and modern orchestration frameworks.
• Integrate AI capabilities into enterprise applications, APIs, databases, cloud platforms, identity providers, messaging systems, and existing technology ecosystems.
• Design reliable AI workflows including tool calling, planning, memory, context engineering, retries, fallback strategies, guardrails, and human-in-the-loop mechanisms.
• Build evaluation pipelines, automated regression testing, golden datasets, and AI observability to continuously measure solution quality.
• Design deployment architectures that prioritize scalability, reliability, maintainability, security, and cost efficiency.
• Troubleshoot production issues, optimize deployed systems, and continuously improve customer solutions.

Required

• Proven ability to work directly with enterprise customers, understand business challenges, and translate them into production-ready AI solutions.
• 5+ years of commercial experience delivering production software systems.
• Strong software engineering fundamentals and proficiency in one or more modern programming languages (such as Java, C#, Python, JavaScript/TypeScript, Go, Kotlin, Rust, Scala, or similar).
• Experience designing distributed, cloud-native, or enterprise applications.
• Hands-on experience with modern LLM platforms such as OpenAI, Anthropic, Google Gemini, Azure OpenAI, Amazon Bedrock, or similar.
• Strong understanding of:
  • Retrieval-Augmented Generation (RAG)
  • Vector databases
  • Embeddings
  • Hybrid search
  • Context engineering
  • Prompt engineering
• Experience building AI-powered applications using modern AI SDKs, orchestration frameworks, or agent platforms (e.g. LangGraph, LangChain, Semantic Kernel, CrewAI, AutoGen, Spring AI, Microsoft AI Extensions, or similar).
• Experience deploying and operating production applications on AWS, Azure, GCP, or other enterprise platforms using modern DevOps and CI/CD practices.
• Solid understanding of enterprise architecture, distributed systems, APIs, integration patterns, networking, identity and access management (IAM), security principles, and modern software delivery practices.
• Ability to balance speed, quality, scalability, maintainability, and cost when making engineering decisions.
• Excellent communication skills and confidence working directly with technical and business stakeholders.
• Upper-Intermediate English or higher.

Nice to Have

• Experience with AI evaluation frameworks, LLM benchmarking, and quality assessment.
• Experience designing golden datasets, automated regression testing, and evaluation pipelines for AI applications.
• Experience with AI observability platforms such as LangSmith, Langfuse, Arize Phoenix, MLflow, or similar.
• Knowledge of AI governance, responsible AI, guardrails, hallucination mitigation, and prompt injection protection.
• Experience with Model Context Protocol (MCP), Agent2Agent (A2A), and emerging AI interoperability standards.
• Experience integrating AI into existing enterprise applications regardless of technology stack.
• Experience with enterprise AI platforms such as Azure AI Foundry, AWS Bedrock, Vertex AI, Databricks, or similar.
• Previous experience in Solution Architecture, Technical Consulting, Customer Engineering, Technical Pre-Sales, or Professional Services.
• Experience working in regulated industries such as healthcare, finance, telecommunications, manufacturing, energy, or the public sector.

Our perks

• Covered vacation period: 20 business days and 5 days off
• Free English classes
• Flexible working schedule
• Truly friendly and supporting atmosphere
• Working remotely or in one of our offices
• Medical insurance for employees from Ukraine
• Legal support