AI Engineer

About The Role

We are seeking talented AI Engineers with a strong blend of communication, stakeholder management, and hands-on expertise in AI agents. The ideal candidate will be adept at articulating solutions to business sponsors, navigating ambiguous requirements with product managers, and coding robust, production-grade agentic workflows. A proactive approach, a commitment to continuous learning, and a keen interest in the evolving agent ecosystem are paramount.

At Flexday AI, you will be instrumental in designing, building, and deploying advanced Agentic AI solutions for major enterprise clients. As a multi-cloud (AWS, Azure, GCP) and multi-LLM (OpenAI, Azure OpenAI, Anthropic, Gemini) AI solutions firm, you will collaborate with global teams throughout the entire development lifecycle, from initial discovery to final production deployment.

Key Responsibilities

• Collaborate with client stakeholders, product owners, and business leads to deeply understand requirements, shape effective solutions, and communicate progress with clarity and credibility.
• Design and develop Agentic AI solutions architected for enterprise-scale deployment.
• Translate functional and business requirements into actionable technical solutions in close partnership with product and business teams.
• Build, test, and deploy AI components across AWS, Azure, or GCP cloud environments.
• Take full end-to-end ownership of features, overseeing development through to production readiness.
• Engage effectively with remote, cross-functional global teams operating across diverse time zones.

Required Skills

• Communication and Stakeholder Management (Primary Requirement)
  • Exceptional written and verbal communication skills in English.
  • Proven ability to demystify complex technical concepts for non-technical business stakeholders.
  • Comfort in facilitating working sessions, leading solution walkthroughs, and managing expectations with client sponsors.
  • Strong sense of ownership, accountability, and dedication to follow-through.
  • Capacity to operate autonomously in dynamic and ambiguous environments.
• Agentic AI (Primary Technical Requirement)
  • Solid working knowledge of AI agents, agentic workflows, and fundamental patterns including tool use, planning, memory, and multi-agent orchestration.
  • Hands-on experience developing agents using frameworks such as LangGraph, LangChain, OpenAI Agents SDK, Semantic Kernel, or comparable technologies (professional or personal projects are valued).
  • Understanding of enterprise-grade agent evaluation, debugging, and productionization techniques.
  • Familiarity with Model Context Protocol (MCP) servers and multi-agent orchestration patterns is highly advantageous.
• AI Specialization (Deep Expertise in At Least One Area)
  • LLM and Generative AI: Prompt engineering, Retrieval Augmented Generation (RAG), fine-tuning, and LLM integration.
  • Machine Learning: Classical ML, feature engineering, model training, evaluation, and deployment.
  • Computer Vision: CNNs, object detection, image segmentation, vision transformers, or Optical Character Recognition (OCR).
• Programming and Software Engineering
  • 2 to 5+ years of hands-on software development experience, with a primary focus on Python.
  • Demonstrated contributions to large-scale programs deployed within enterprise settings.
  • Understanding of full-stack development principles, REST APIs, and microservices architecture.
  • Commitment to code quality, comprehensive testing, and thorough documentation.
• Cloud and Data
  • Hands-on experience developing and deploying solutions on AWS or Azure; GCP experience is a plus.
  • Experience working with large datasets and managing data pipelines.
  • Familiarity with containerization using Docker and version control with Git.

Good to Have

• Enterprise Platforms
  • Amazon Bedrock and Amazon Bedrock AgentCore
  • Microsoft Copilot and Copilot Studio
  • Azure OpenAI, Azure AI Foundry, or Google Vertex AI
• Agent Frameworks and Protocols
  • LangGraph, LangChain, OpenAI Agents SDK, or similar libraries.
  • Model Context Protocol (MCP) servers and multi-agent orchestration.
• RAG and Retrieval Systems
  • Vector databases (e.g., Pinecone, Weaviate, Qdrant, pgvector).
  • Experience with embedding pipelines, semantic search, and document intelligence.
• Data Engineering
  • Proficiency with platforms like Databricks, PySpark, Microsoft Fabric, or Synapse, along with a solid grasp of underlying concepts.
• DevOps and MLOps
  • Understanding of Continuous Integration/Continuous Deployment (CI/CD), model deployment, monitoring, and observability.
  • Hands-on experience with leading MLOps tools and platforms.

Qualifications

• Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related technical field from a reputable institution.
• A PhD or equivalent qualification is highly regarded, and candidates with doctoral backgrounds are strongly encouraged to apply.

Why Flexday AI

Flexday AI is a forward-thinking multi-cloud, multi-LLM AI solutions firm, partnering with Fortune 500 clients to implement transformative enterprise AI. You will have the opportunity to work directly with senior engineering and client teams, assume ownership of impactful features, and experience rapid professional growth within a high-trust, high-accountability environment.