Key skills
JavaScriptTypeScriptPythonAIMLLLMOpenAIClaudeLlamaRAGLangChainLlamaIndexAgenticAutoGenPineconeWeaviateReactFastAPIGraphQLAzureGitVersion ControlPerformance Optimization
About this role
AI Engineer (3+ Years Experience)
What you’ll do
As an AI Engineer, you will design, build, and implement AI-powered applications, intelligent agents, and LLM-driven solutions that address real business problems. You will work hands-on developing AI workflows, building conversational AI systems, implementing RAG pipelines, integrating enterprise APIs, and optimizing model outputs for performance and usability. This role focuses on engineering and development rather than operations — translating product requirements into scalable AI architectures, writing production-grade code, and delivering AI-powered features that integrate seamlessly into enterprise systems. You will collaborate closely with product, UX, backend, and frontend teams to deliver impactful AI capabilities.
What you’ll bring
- 3+ years of hands-on software development experience
- At least 3+ years working directly with AI/ML or LLM-based applications
- Strong programming background in building scalable applications
- Experience designing and shipping AI-powered products or features
- Ability to independently translate requirements into AI solutions
- Familiarity with cloud platforms (Azure preferred)
- Degree in Computer Science, Engineering, Data Science, or equivalent practical experience
Skill Requirements
- Strong experience building AI agents, conversational AI, or LLM-powered applications
- Hands-on experience with agentic AI frameworks such as LangChain, LlamaIndex, Semantic Kernel, AutoGen, CrewAI, or similar frameworks
- Experience designing RAG pipelines and integrating enterprise knowledge sources
- Experience working with foundation models such as GPT-4, Claude, Llama, or similar LLMs
- Understanding of prompt engineering, embeddings, context handling, and function calling
- Experience with vector databases such as Pinecone, Weaviate, FAISS, or Azure AI Search
- Strong Python development skills (FastAPI, async programming, ML libraries preferred)
- Experience with Typescript/JavaScript and React for AI-integrated applications
- API design and integration experience (REST, GraphQL, enterprise APIs)
- Familiarity with Azure AI services including Azure OpenAI and related tooling
- Strong understanding of software architecture, modular design, and clean coding practices
- Experience with Git, version control, and collaborative engineering workflows
- Strong testing, debugging, and performance optimization skills
Typical AI Engineer Roles and Responsibilities
- Build AI agents and AI-powered applications from product requirements
- Develop prompts, evaluation frameworks, and optimization strategies
- Implement RAG pipelines and integrate enterprise data sources
- Build backend services supporting AI workflows and APIs
- Test AI systems across real-world use cases and edge scenarios
- Optimize model performance, response quality, and latency
- Collaborate with frontend/backend teams to integrate AI features
- Experiment with emerging AI frameworks, tools, and models
- Maintain reusable AI components, documentation, and code quality standards
AI Engineer (3+ Years Experience)
What you’ll do
As an AI Engineer, you will design, build, and implement AI-powered applications, intelligent agents, and LLM-driven solutions that address real business problems. You will work hands-on developing AI workflows, building conversational AI systems, implementing RAG pipelines, integrating enterprise APIs, and optimizing model outputs for performance and usability. This role focuses on engineering and development rather than operations — translating product requirements into scalable AI architectures, writing production-grade code, and delivering AI-powered features that integrate seamlessly into enterprise systems. You will collaborate closely with product, UX, backend, and frontend teams to deliver impactful AI capabilities.
What you’ll bring
- 3+ years of hands-on software development experience
- At least 3+ years working directly with AI/ML or LLM-based applications
- Strong programming background in building scalable applications
- Experience designing and shipping AI-powered products or features
- Ability to independently translate requirements into AI solutions
- Familiarity with cloud platforms (Azure preferred)
- Degree in Computer Science, Engineering, Data Science, or equivalent practical experience
Skill Requirements
- Strong experience building AI agents, conversational AI, or LLM-powered applications
- Hands-on experience with agentic AI frameworks such as LangChain, LlamaIndex, Semantic Kernel, AutoGen, CrewAI, or similar frameworks
- Experience designing RAG pipelines and integrating enterprise knowledge sources
- Experience working with foundation models such as GPT-4, Claude, Llama, or similar LLMs
- Understanding of prompt engineering, embeddings, context handling, and function calling
- Experience with vector databases such as Pinecone, Weaviate, FAISS, or Azure AI Search
- Strong Python development skills (FastAPI, async programming, ML libraries preferred)
- Experience with Typescript/JavaScript and React for AI-integrated applications
- API design and integration experience (REST, GraphQL, enterprise APIs)
- Familiarity with Azure AI services including Azure OpenAI and related tooling
- Strong understanding of software architecture, modular design, and clean coding practices
- Experience with Git, version control, and collaborative engineering workflows
- Strong testing, debugging, and performance optimization skills
Typical AI Engineer Roles and Responsibilities
- Build AI agents and AI-powered applications from product requirements
- Develop prompts, evaluation frameworks, and optimization strategies
- Implement RAG pipelines and integrate enterprise data sources
- Build backend services supporting AI workflows and APIs
- Test AI systems across real-world use cases and edge scenarios
- Optimize model performance, response quality, and latency
- Collaborate with frontend/backend teams to integrate AI features
- Experiment with emerging AI frameworks, tools, and models
- Maintain reusable AI components, documentation, and code quality standards