2–5 years of experience in software engineering, AI engineering, or ML systems
Nice to have6
MCP architectures or tool-connected AI systems
Agent frameworks
Knowledge graph systems
Streaming or event-driven systems
Distributed systems design
Evaluation frameworks for AI systems
Skills
Python
TypeScript
REST APIs
OpenAI API
Anthropic API
LLM gateway
Vector databases
Agent orchestration frameworks
MCP
Docker
AWS
GCP
Azure
CI/CD
Pinecone
Weaviate
pgvector
Knowledge graph systems
About the role
SLR is seeking an AI Development Engineer who enjoys building AI systems that operate reliably in the real world. This role sits at the intersection of AI engineering, software development, and infrastructure, focusing on designing and implementing production-grade systems powered by large language models (LLMs).
You will work hands-on across the full delivery lifecycle—moving quickly from concept to prototype to production. Working closely with product, engineering, and data teams, you will help deliver intelligent applications built on modern AI infrastructure.
About the company
We value practical builders over academic theory. Success in this role is defined by your ability to design, implement, deploy, and operate real systems that deliver business value.
What You Will Build
You will design and implement systems across the AI stack, including:
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LLM-powered applications and intelligent agents
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Model orchestration and tool-use frameworks
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Retrieval systems and knowledge layers (RAG)
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MCP-style integration layers connecting models to tools, APIs, and data sources
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Scalable infrastructure supporting AI workloads
Your work will progress rapidly from prototype to production, with real users and real constraints.
Key Responsibilities
Build AI Systems
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Design and implement production-grade systems powered by LLMs and modern AI frameworks
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Develop applications using technologies such as:
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OpenAI, Anthropic and other LLM APIs
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LLM gateway
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Vector databases
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Agent orchestration frameworks
Implement AI Infrastructure
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Build and operate the infrastructure required to run reliable AI services, including:
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API services supporting AI applications
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Orchestration layers between models and tools
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Retrieval pipelines and knowledge indexing
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Observability and monitoring for AI systems
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Scalable backend services
Develop MCP and Tool Integration Layers
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Design integration layers that enable models to interact with external systems, including:
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API integrations
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Tool-use systems for agents
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Connectors to databases, SaaS tools, or internal platforms
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Structured prompting and function-calling architectures
Ship Production Code
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Move quickly from concept to working product
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Write clean, maintainable backend code
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Build testable services
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Deploy systems in production environments
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Iterate based on real user feedback
Collaborate Across Teams
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Work closely with product managers, engineers, and designers to turn ideas into working solutions
Required Skills
Software Engineering Foundations
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Strong backend engineering experience
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Proficiency in Python (preferred) or TypeScript
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Experience building REST APIs and backend services
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Solid system design fundamentals
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Debugging and production troubleshooting skills
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Understand software development lifecycle
LLM Application Development
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Experience building applications using large language models