AI Engineer

Akaasa Technologies; California; On-site; USD 120,000 - 165,000; Full time

Job summary

Akaasa Technologies in California seeks an AI Engineer to design, develop, deploy, and operate enterprise AI solutions. You will build intelligent assistants, agents, and generative AI applications using Azure AI Foundry, Copilot Studio, and Power Platform, collaborating with architects, data engineers, and product teams.

You will balance low-code and pro-code approaches, implement RAG pipelines, and ensure security, governance, and responsible AI.

Qualifications

• At least four years of software engineering, AI/ML development, or related technical experience.
• Hands-on experience deploying AI/ML solutions in production.
• Microsoft Azure AI experience including Azure AI Foundry, Azure OpenAI, and Azure AI Search.
• Experience delivering agents in Copilot Studio and Azure Foundry Agent Service.
• Experience with Power Automate, Power Apps, and Dataverse integrations.
• Strong understanding of generative AI, RAG, prompt engineering, vector databases, knowledge grounding, and orchestration patterns.
• Strong Python development experience.
• Experience with LangGraph, LangChain, and OpenAI or Azure OpenAI SDKs.
• Experience developing and integrating APIs and REST services.
• Familiarity with MuleSoft, Azure API Management, or Microsoft Graph connectors.
• Knowledge of AI gateways, Model Context Protocol, agent interoperability, and tool orchestration.
• Experience with Git, GitHub Copilot, Visual Studio Code, CI/CD pipelines, testing, debugging, and modern DevOps practices.
• Understanding of AI security, data privacy, responsible AI, regulatory compliance, and AI FinOps.
• Strong communication, collaboration, analytical thinking, and problem solving.

Responsibilities

• Design, build, test, deploy, and support AI assistants and agents using Copilot Studio and Azure AI Foundry Agent Service.
• Determine whether low-code or pro-code development is most appropriate for each solution.
• Build agentic workflows and multi-agent orchestration using Copilot Studio, Power Platform, Python, SDKs, and APIs.
• Develop RAG pipelines involving data ingestion, vector indexing, prompt engineering, knowledge grounding, and enterprise data sources.
• Participate throughout the SDLC, including requirements, design, development, testing, deployment, and production support.
• Write clean, maintainable, and well-documented code.
• Support CI/CD pipelines and LLMOps practices for models, prompts, and agent lifecycles.
• Integrate AI solutions with Cosmos DB, Dataverse, SQL databases, file systems, SaaS platforms, and other enterprise applications.
• Work with MuleSoft, Azure API Management, Azure Integration Services, Microsoft Graph connectors, AI gateways, and MCP.
• Implement security, privacy, responsible AI, content-filtering, and governance controls.
• Participate in architecture reviews, delivery planning, estimation, technical demonstrations, workshops, and documentation.

Skills

Python development

LangChain

OpenAI SDKs

Azure AI services

Copilot Studio

Power Platform

Dataverse integration

API development

REST services

Git / GitHub Copilot

CI/CD

DevOps practices

Problem solving

Communication

Education

Bachelor's degree in Computer Science, Information Systems, Software Engineering, or a related technical discipline

Tools

Azure OpenAI

Azure AI Foundry

Azure AI Search

Copilot Studio

Power Platform

Dataverse

MuleSoft

Microsoft Graph connectors

Azure API Management

Microsoft Graph

VS Code

Job description

AI Engineer

Reason for position

Seeking an AI Engineer to support the hands‑on design, development, deployment, and operational support of enterprise AI solutions. The role will help deliver scalable digital assistants, AI agents, generative AI applications, computer vision solutions, and intelligent process automation that improve productivity, customer experience, and operational efficiency.

Team Overview

The position sits within the Enterprise Architecture and Artificial Intelligence team. The engineer will collaborate closely with enterprise and solution architects, data engineers, business analysts, product managers, business stakeholders, and external technology partners.

Project Description

Design and deliver production‑grade AI solutions using the Microsoft AI ecosystem, including Azure AI Foundry, Azure OpenAI, Azure AI Search, Copilot Studio, Power Platform, and Azure services. The portfolio may include:

• Intelligent digital assistants and AI agents
• Agentic and multi‑agent workflows
• Retrieval‑augmented generation solutions
• Generative AI applications
• Computer vision and video analytics
• Intelligent process automation
• Demand forecasting and personalization use cases
• Enterprise system and data integrations

Duties/Day to Day Overview

Design, build, test, deploy, and support AI assistants and agents using Copilot Studio and Azure AI Foundry Agent Service.

Determine whether low‑code or pro‑code development is most appropriate for each solution.

Build agentic workflows and multi‑agent orchestration using Copilot Studio, Power Platform, Python, SDKs, and APIs.

Develop RAG pipelines involving data ingestion, vector indexing, prompt engineering, knowledge grounding, and enterprise data sources.

Participate throughout the SDLC, including requirements, design, development, testing, deployment, and production support.

Write clean, maintainable, and well‑documented code.

Support CI/CD pipelines and LLMOps practices for models, prompts, and agent lifecycles.

Integrate AI solutions with Cosmos DB, Dataverse, SQL databases, file systems, SaaS platforms, and other enterprise applications.

Work with MuleSoft, Azure API Management, Azure Integration Services, Microsoft Graph connectors, AI gateways, and MCP.

Implement security, privacy, responsible AI, content‑filtering, and governance controls.

Participate in architecture reviews, delivery planning, estimation, technical demonstrations, workshops, and documentation.

Top Requirements

(Must haves)

• At least four years of software engineering, AI/ML development, or related technical experience.
• Hands‑on experience developing and deploying AI/ML or intelligent automation solutions in production or near‑production environments.
• Microsoft Azure AI experience, including Azure AI Foundry, Azure OpenAI, and Azure AI Search.
• Hands‑on experience building and delivering agents in both Copilot Studio and Azure AI Foundry Agent Service.
• Experience with Power Automate, Power Apps, and Dataverse integrations.
• Strong understanding of generative AI, RAG, prompt engineering, vector databases, knowledge grounding, and orchestration patterns.
• Strong Python development experience.
• Experience with LangGraph, LangChain, and OpenAI or Azure OpenAI SDKs.
• Experience developing and integrating APIs and REST services.
• Familiarity with MuleSoft, Azure API Management, or Microsoft Graph connectors.
• Working knowledge of AI gateways, Model Context Protocol, agent interoperability, and tool orchestration.
• Experience with Git, GitHub Copilot, Visual Studio Code, CI/CD pipelines, testing, debugging, and modern DevOps practices.
• Understanding of AI security, data privacy, responsible AI, regulatory compliance, and AI FinOps.
• Strong communication, collaboration, analytical thinking, and problem‑solving skills.
• Bachelor's degree in Computer Science, Information Systems, Software Engineering, or a related technical discipline.

Additional Qualifications

(Nice to Haves)

• Microsoft Azure AI Engineer Associate certification
• Microsoft Power Platform Developer Associate certification
• Microsoft Azure Developer Associate certification
• Computer vision experience with Azure AI Vision, Azure AI Video Indexer, or OpenCV
• Experience with AutoGen or other multi‑agent orchestration frameworks
• Exposure to LLMOps tooling and production lifecycle management
• Retail technology experience, particularly within store operations, customer experience, supply chain, or merchandising

Additional Notes

This is a hands‑on engineering position requiring both low‑code and pro‑code capabilities.

Candidates should have practical experience delivering agents through Copilot Studio and Azure AI Foundry, not solely conceptual or architectural AI experience.

The position spans the complete solution lifecycle and includes post‑production support.

The environment requires close coordination across architecture, engineering, product, business, and external partner teams.

Candidates should be comfortable working with rapidly evolving AI technologies and applying them to enterprise retail use cases.