AI Engineer

Introduction

Robosoft is expanding its AI engineering capability, building real applications and agentic systems that create measurable business value. The AI Engineer works closely with internal teams across Robosoft to understand real business problems, then designs, builds, and deploys AI-powered applications and agents that improve how we work.

This is a hands-on software engineering role, not a configuration or low-code position. You will write Python code every day, build backend services and APIs with Fast API, wire together frontend interfaces, work with databases, and integrate LLM SDKs to create intelligent, production-ready applications. You will work closely with a senior AI Solutions Engineer and internal stakeholders, owning deployments end-to-end, from requirements through to production go-live.

If you have a software or data engineering background and are excited about building with AI frameworks like the Claude SDK, creating multi-agent systems, and owning the full SDLC of AI-native products, this role is for you. If you are someone who is not just interested in the future – but wants to be part of building it – then this is the right role for you.

Responsibilities

AI Application Development

• Build backend services and REST APIs using Python and Fast API that power AI Agent native applications
• Integrate the Claude SDK (Anthropic) and other LLM SDKs into applications to create conversational, agentic, and automation workflows
• Develop and maintain lightweight frontend interfaces (React, Next, HTML/JS) that expose AI functionality to end users
• Manage data persistence layers: design schemas, write queries, and work with relational and NoSQL databases
• Own features end-to-end, from requirements and design through implementation, testing, and deployment
• Work with open-source LLMs (e.g., Llama, Mistral) where data-residency, privacy, or cost constraints require self-hosted models

Agentic Systems and Multi-Agent Engineering

• Build and manage AI subagents and orchestrated agent pipelines using the Claude SDK and related frameworks
• Implement tool use, function calling, and context management patterns for complex agentic tasks
• Design and maintain prompt architectures, system prompts, and agent routing logic
• Contribute to the engineering of multi-agent systems that handle real-world workflows autonomously

Evaluation and Quality Engineering

• Build and run evaluation frameworks to assess AI application quality, accuracy, and safety
• Design test cases and automated eval suites to measure model and agent performance against defined criteria
• Track regressions, log outputs, and contribute to continuous improvement of AI systems in production
• Ensure applications meet quality standards before release through structured testing and review processes

Deployment and Adoption

• Build rapid prototypes and proofs of concept to validate the approach with internal stakeholders before committing to full builds
• Deploy and integrate solutions into Robosoft’s internal environments (enterprise systems, data sources, SSO/identity, and cloud or on-prem infrastructure) via APIs, plugins, connectors, and MCP servers
• Feed learnings back into Robosoft’s reusable accelerators, internal tooling, and engineering playbooks

Documentation and Knowledge Sharing

• Write clear technical documentation for APIs, applications, agent architectures, and eval frameworks
• Maintain architecture decision records (ADRs) and engineering notes for projects you own
• Share learnings with the team and contribute to internal standards and best practices

Requirements

• 7+ years of experience in software engineering, backend development, or data engineering
• Strong Python skills: comfortable writing production-quality Python code
• Experience building and consuming REST APIs; understanding of HTTP, request/response cycles, and authentication patterns
• Familiarity with the SDLC: requirements, design, implementation, testing, deployment, and maintenance
• Working knowledge of relational databases (PostgreSQL, MySQL) and ability to write SQL queries
• Basic frontend development ability: comfortable building functional UIs in React or vanilla HTML/JS
• Comfortable using Git, version control workflows, and code review processes
• Experience working with business stakeholders: gathering requirements and presenting solutions
• Strong written and verbal communication skills; comfortable presenting technical concepts to non-technical audiences

Core Skills

• Technical Skills: Python (data structures, OOP, async programming, packaging, testing), Fast API (or equivalent) for building REST APIs, LLM/AI SDK integration, database fundamentals, RESTful API design, automated testing (unit and integration), and Docker-based deployment with CI/CD basics on at least one cloud platform (AWS, Azure, or GCP)
• Tools and Technologies: Claude SDK (Anthropic), Claude Agent SDK and managed subagents, PostgreSQL, Click house, Qdrant (vector database), React, Next, Git, GitHub, Docker, VS Code / Cursor
• Soft Skills: Clear technical and business communication, stakeholder collaboration, self-direction, and outcome ownership through to production

Good to Have Skills

• Direct experience with the Claude SDK (Anthropic) or similar LLM SDKs (e.g., Cursor)
• Experience building agentic or multi-agent systems: tool use, function calling, orchestration
• Familiarity with AI evaluation frameworks or experience designing eval pipelines
• Cursor or AI-assisted coding environments as a core part of your workflow
• Enterprise integration experience: SSO/OAuth, SharePoint, Salesforce, ServiceNow, or similar platforms
• Data engineering exposure: ETL pipelines, data transformation, working with structured and unstructured data
• MCP (Model Context Protocol) server development