Understand the system design and provide impact analysis to any changes.
Perform application health check and monitoring
Required to work on shifts on a rotational basis to provide 18 by 7 support with 2 days off. (9 hours per shift – 6:30am to 3:30pm/ 2:30pm to 11:30pm)
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You will work across the entire stack — from frontend experiences and APIs to distributed systems, data infrastructure, LLM orchestration, agentic workflows, evaluation systems, and autonomous optimization loops.
The ideal candidate has deep hands-on experience with Claude/Anthropic models, agentic architectures, tool-use, multi-step reasoning, autonomous execution loops, and AI-driven self-optimization.
You should be comfortable asking: "How can we make the system improve itself rather than requiring an engineer to manually optimize every workflow?"
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You will work across the entire stack — from frontend experiences and APIs to distributed systems, data infrastructure, LLM orchestration, agentic workflows, evaluation systems, and autonomous optimization loops.
The ideal candidate has deep hands-on experience with Claude/Anthropic models, agentic architectures, tool-use, multi-step reasoning, autonomous execution loops, and AI-driven self-optimization.
You should be comfortable asking: "How can we make the system improve itself rather than requiring an engineer to manually optimize every workflow?"
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Job SummaryWe are looking for a hands-on AI Engineer to design, develop, integrate, and deploy Generative AI, AI chatbot, and Agentic AI solutions. The role will focus on building practical AI applications and integrating LLM capabilities with existing applications, APIs, databases, and enterprise systems.Key ResponsibilitiesDesign and develop AI chatbots, copilots, and LLM-powered applications.Build Agentic AI solutions with reasoning, tool/function calling, multi-step task execution, and workflow automation.Implement RAG, embeddings, vector search, prompt engineering, and conversational memory.Work with commercial and open-source LLMs and select appropriate models based on business and technical requirements.Integrate AI solutions with REST APIs, databases, CRM/ERP systems, and enterprise applications.Develop AI integration services and APIs for existing systems and business workflows.Evaluate and optimize AI solutions for accuracy, reliability, latency, scalability, security, and cost.Collaborate with software engineers, architects, product teams, and business stakeholders.Keep up to date with developments in Generative AI, LLMs, Agentic AI, and AI automation.RequirementsBachelor's degree in Computer Science, AI/ML, Software Engineering, or a related field.3+ years of experience in AI/ML engineering, software engineering, or a related role.Hands-on experience developing LLM applications, AI chatbots, or Generative AI solutions.Practical experience with AI Agents, Agentic AI, tool/function calling, or AI workflow automation.Experience with open-source LLMs such as Llama, Qwen, Mistral, Gemma, or equivalent.Strong Python programming and software engineering skills.Experience with REST APIs, system integration, databases, and cloud/on-premise environments.Hands-on experience with RAG, vector databases, embeddings, and prompt engineering.Experience with frameworks such as LangChain, LangGraph, LlamaIndex, Semantic Kernel, AutoGen, CrewAI, or equivalent.Experience with LLM platforms such as OpenAI, Azure OpenAI, Anthropic, Gemini, and/or open-source models.Familiarity with Docker, Git, CI/CD, and production deployment.Preferred SkillsExperience serving open-source LLMs using vLLM, Hugging Face, Ollama, or equivalent.Experience with MCP, multi-agent systems, LLM evaluation/observability, fine-tuning, LoRA/QLoRA, or model optimization.Experience with AWS, Azure, or Google Cloud.Knowledge of AI security, data privacy, access control, and responsible AI.
Full Stack EngineeringFrontend: React, Next.js, TypeScript, modern component architectures, state management, real-time and streaming AI interfaces, agent activity and execution interfaces, data visualization.Backend: Node.js, TypeScript, Python, REST APIs, GraphQL, WebSockets and streaming, event-driven architectures, background workers, job queues, distributed systems, authentication and authorization.
Distributed SystemsDesign systems that reliably execute thousands or millions of AI and data-processing tasks. Kubernetes, Docker, Cloud Run and serverless, message queues, Redis, Kafka or equivalent, distributed job processing, concurrency management, rate limiting, retries, idempotency, fault tolerance, observability. You know how to build systems that stay reliable when agents fail, APIs time out, models hallucinate, or downstream services go away.
Data & Learning InfrastructureBuild the infrastructure agents need to learn from historical executions. PostgreSQL, BigQuery or equivalent data warehouses, ClickHouse or analytical databases, vector databases, embeddings, retrieval systems, event logs, feature stores, analytics pipelines, data ingestion.
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Integrate applications using Java, SQL, Web Services, APIs and Windows Batch Scripts.
Work closely with Business Analysts, System Analysts, Solution Architects and business users to understand requirements and assess technical feasibility.
Translate functional requirements into technical specifications, solution designs and impact assessments.
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We are looking at hiring two specialists. One role is focused on the services and API side: designing endpoints, building backend logic, owning data models, and making sure things are fast and reliable. A second engineer on the team will focus on integrations and infrastructure - you'll work alongside another junior engineer in a Team of 3.
Role Description
As an experienced Backend Engineer, you will design, build, and maintain server-side applications and services that power our digital infrastructure.
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