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Associate Program Manager Description We are seeking a Lead Forward Deployed AI Engineer to architect and deliver enterprise-scale AI transformation programs. This role combines deep technical expertise with solution architecture, delivery leadership, and customer engagement to build scalable AI platforms that drive business innovation. The ideal candidate will be a techno-functional leader with extensive experience in Generative AI, Agentic AI, LLMs, AI platform engineering, enterprise solutioning, and large-scale customer engagements. You will lead technical teams, mentor engineers, and work closely with CXOs and business leaders to deliver AI-powered transformation initiatives. Key Responsibilities Lead the design, architecture, and deployment of enterprise AI solutions leveraging Generative AI, Agentic AI, LLMs, RAG, and AI Agents. Partner with clients to define AI strategies, solution roadmaps, and enterprise AI adoption plans. Lead AI solutioning, architecture workshops, and technical discovery sessions. Drive AI-enabled transformation across business operations and Software Development Lifecycle (SDLC). Architect intelligent automation and multi-agent solutions using LangGraph, CrewAI, LangChain, Azure AI Foundry, AWS Bedrock, Google Gemini Enterprise, and similar platforms. Optimize AI platforms for performance, accuracy, scalability, latency, and operational cost. Lead cross-functional engineering teams across AI, Data Science, Platform Engineering, and DevOps. Establish engineering standards, architecture governance, code reviews, and AI best practices. Mentor engineering teams and promote innovation across enterprise AI programs. Support pre-sales, solution consulting, executive presentations, and strategic client engagements. Required Skills & Qualifications 13+ years of experience in Software Engineering, AI Engineering, Solution Architecture, or Enterprise Technology. Proven experience leading enterprise AI delivery and customer-facing engagements. Strong expertise in LLMs, Agentic AI, Generative AI, RAG, Prompt Engineering, AI Agents, and AI orchestration frameworks. Hands-on experience with LangGraph, CrewAI, LangChain, LlamaIndex, or similar platforms. Strong knowledge of AWS Bedrock, Azure AI Foundry, Google Gemini Enterprise, and enterprise AI ecosystems. Experience building scalable AI platforms using Python, Hugging Face, PyTorch, TensorFlow, and modern AI frameworks. Strong understanding of software architecture, APIs, microservices, distributed systems, and cloud-native development. Experience leading technical teams and mentoring engineers. Excellent communication, stakeholder management, consulting, and client engagement skills. Preferred Skills Experience with MLOps, LLMOps, AI governance, and Responsible AI. Expertise in PEFT, LoRA, QLoRA, model optimization, and inference acceleration. Experience contributing to AI platform strategy, innovation, or enterprise AI Centers of Excellence (CoEs). .
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.