Job description

Ampcus Inc. is a certified global provider of a broad range of Technology and Business consulting services. We are in search of a highly motivated candidate to join our talented Team. Role Overview We are seeking an experienced Senior AI Architect to lead the design, development, and deployment of next-generation Generative AI and Agentic AI solutions . The ideal candidate will have deep expertise in Retrieval-Augmented Generation (RAG) pipelines, AI coding assistants such as Claude Code, OpenAI Codex, and Cline , and experience building autonomous AI agents capable of reasoning, planning, and executing complex business workflows. This role requires a hands-on technical leader who can define AI strategy, architect enterprise-grade AI platforms, guide engineering teams, and drive innovation across GenAI, LLMOps, and intelligent agent ecosystems. Key Responsibilities AI & GenAI Architecture • Design and implement enterprise-scale Generative AI solutions using Large Language Models (LLMs). • Architect advanced RAG-based systems incorporating vector databases, semantic search, enterprise knowledge repositories, and hybrid retrieval models. • Define scalable AI architectures covering data ingestion, embeddings, retrieval, orchestration, guardrails, observability, and evaluation frameworks. • Establish AI governance, security, compliance, and responsible AI practices. Agentic AI & Autonomous Systems • Design and develop multi-agent and Agentic AI solutions capable of planning, reasoning, tool usage, memory management, and workflow orchestration. • Build autonomous agents using frameworks such as: • LangGraph • CrewAI • AutoGen • Semantic Kernel • OpenAI Agents SDK • LangChain • Implement agent collaboration, human-in-the-loop workflows, and agent monitoring mechanisms. RAG Engineering • Architect and optimize: • Knowledge ingestion pipelines • Document chunking strategies • Embedding architectures • Query optimization • Re-ranking models • Hybrid search implementations • Work with vector databases such as: • Pinecone • Weaviate • Qdrant • Chroma • Azure AI Search • Elasticsearch/OpenSearch AI Coding Platforms & Developer Productivity • Lead adoption and integration of AI-assisted development tools including: • Claude Code • OpenAI Codex • Cline • GitHub Copilot • Cursor • Define standards and best practices for AI-driven software engineering and code generation workflows. • Architect AI-powered SDLC automation capabilities. LLMOps & Platform Engineering • Build robust CI/CD pipelines for AI applications. • Implement: • Model evaluation frameworks • Prompt management • Experiment tracking • Cost optimization • AI observability • Production monitoring • Establish enterprise LLMOps standards and governance models. Technical Leadership • Mentor architects, engineers, and AI specialists. • Define technology roadmaps and AI strategy aligned with business objectives. • Engage with stakeholders, product teams, and executive leadership to translate business challenges into AI solutions. • Evaluate emerging AI technologies and recommend adoption strategies. Required Qualifications Education • Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related field. Experience • 12 years of overall software engineering experience. • 5 years in AI/ML solution architecture. • 2 years building production-grade Generative AI applications. • Proven experience delivering enterprise-scale AI platforms. Technical Skills Generative AI & LLMs • GPT-4/5 • Claude • Gemini • Llama • Mistral • DeepSeek • Open-source LLM ecosystems RAG Technologies • LangChain • LlamaIndex • Vector databases • Embeddings • Semantic Search • Knowledge Graphs • Hybrid Retrieval Agentic AI • LangGraph • CrewAI • AutoGen • Semantic Kernel • MCP (Model Context Protocol) • Tool Calling • Function Calling • Agent Memory Architectures Programming Languages • Python (Expert) • JavaScript / TypeScript • C# • Java (Preferred) Cloud Platforms • Microsoft Azure (Preferred) • Azure AI Foundry • Azure OpenAI • AWS Bedrock • Google Vertex AI DevOps & MLOps • Docker • Kubernetes • GitHub Actions • Jenkins • Terraform • MLflow • Weights & Biases Databases • PostgreSQL • MongoDB • Cosmos DB • Redis • Neo4j • Vector Databases Preferred Certifications • Microsoft Certified: Azure AI Engineer Associate • Azure Solutions Architect Expert • AWS Machine Learning Specialty • Google Professional Machine Learning Engineer • Databricks Generative AI Certification Ampcus is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, protected veterans or individuals with disabilities.

Requirements

Must-haves

Ampcus Inc. is a certified global provider of a broad range of Technology and Business consulting services. We are in search of a highly motivated candidate to join our talented Team.
AI & GenAI Architecture
Design and implement enterprise-scale Generative AI solutions using Large Language Models (LLMs).
Architect advanced RAG-based systems incorporating vector databases, semantic search, enterprise knowledge repositories, and hybrid retrieval models.
Define scalable AI architectures covering data ingestion, embeddings, retrieval, orchestration, guardrails, observability, and evaluation frameworks.
Establish AI governance, security, compliance, and responsible AI practices.
Agentic AI & Autonomous Systems
Design and develop multi-agent and Agentic AI solutions capable of planning, reasoning, tool usage, memory management, and workflow orchestration.
Build autonomous agents using frameworks such as:
Semantic Kernel
OpenAI Agents SDK
Implement agent collaboration, human-in-the-loop workflows, and agent monitoring mechanisms.
RAG Engineering
Knowledge ingestion pipelines
Document chunking strategies
Embedding architectures
Query optimization
Re-ranking models
Hybrid search implementations
Azure AI Search
Elasticsearch/OpenSearch
AI Coding Platforms & Developer Productivity
Lead adoption and integration of AI-assisted development tools including:
OpenAI Codex

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

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Effort: medium