Role Overview:
We are looking for a talented Forward Deployed AI Engineer with a passion for software engineering, Generative AI, Agentic AI, and enterprise AI transformation. In this client-facing role, you will work directly with customers to design, build, deploy, and scale production-grade AI solutions that solve complex business challenges.
You will act as the bridge between business and technology, partnering with stakeholders to transform organizations through AI-powered applications, intelligent automation, and modern AI platforms.
Key Responsibilities:
Design, develop, and deploy enterprise AI solutions leveraging Generative AI, Agentic AI, LLMs, SLMs, and RAG.
Work closely with customers to understand business problems and translate them into scalable AI solutions.
Develop AI-powered applications for conversational AI, intelligent automation, and AI-assisted Software Development Lifecycle (SDLC).
Build production-ready AI workflows using LangGraph, CrewAI, LangChain, Azure AI Foundry, AWS Bedrock, Google Gemini Enterprise, and similar AI platforms.
Design agent orchestration frameworks integrating enterprise systems, APIs, databases, and external tools.
Optimize AI solutions for accuracy, latency, scalability, reliability, and cost efficiency.
Build robust APIs, microservices, and AI services following software engineering best practices.
Collaborate with Product, Engineering, Data Science, and DevOps teams to deliver enterprise AI platforms.
Participate in customer workshops, solution design, PoCs, technical discussions, and deployment activities.
Contribute to continuous improvement by evaluating emerging AI technologies and recommending innovative solutions.
Required Skills & Qualifications:
7–13 years of experience in Software Engineering, AI Engineering, or Machine Learning.
Strong programming expertise in Python.
Hands-on experience with LLMs, Agentic AI, Generative AI, RAG, Prompt Engineering, and AI Agents.
Experience with AI frameworks such as LangGraph, LangChain, CrewAI, LlamaIndex, or similar orchestration platforms.
Knowledge of AWS Bedrock, Azure AI Foundry, Google Gemini Enterprise, or equivalent AI platforms.
Experience with PyTorch, TensorFlow, Hugging Face, or modern AI frameworks.
Strong understanding of vector databases, embeddings, semantic search, and AI workflows.
Experience with Docker, Kubernetes, REST APIs, CI/CD, and cloud platforms (AWS, Azure, or GCP).
Strong communication skills with experience working directly with enterprise clients.
Experience working in Agile development environments.
Preferred Skills:
Experience with MLOps/LLMOps and AI deployment frameworks.
Exposure to PEFT, LoRA, QLoRA, or model optimization techniques.
Knowledge of distributed computing and enterprise AI infrastructure.