Lead Applied AI Engineer – Language Models & AWS MLOps

Work Type: Full Time
Experience

Required:

8 years software engineering with AI/ML focus, 3 years technical leadership

• Our client is a leading technology consulting firm specializing in intelligent systems and AI-powered solutions. They work with enterprise clients to architect and deploy cutting-edge AI applications, from generative AI copilots to complex machine learning pipelines, helping organizations transform their operations through advanced artificial intelligence.

• Join as a Senior AI Engineer leading the architecture and implementation of advanced AI and machine learning systems that solve complex business problems. You’ll work at the forefront of generative AI, building LLM-based applications, AI copilots, and intelligent workflows while mentoring engineering teams and driving AI strategy for enterprise clients.

• Architect and implement advanced AI/ML systems solving complex business challenges
• Lead design and deployment of LLM-based applications using Lang Chain, Llama Index, and vector databases
• Develop end-to-end ML pipelines from data acquisition and model training to deployment and monitoring
• Design and build AI copilots, agents, and generative workflows integrated into modern software ecosystems
• Apply deep expertise in NLP, computer vision, or predictive modeling for intelligent, real-time systems
• Evaluate and fine-tune foundation models for custom enterprise use cases
• Collaborate with cross-functional teams (product, design, engineering) to define intelligent experiences
• Implement RAG, semantic search, and multi-modal reasoning technologies
• Contribute to internal AI frameworks and accelerators to speed solution delivery
• Mentor engineers on AI architecture, model lifecycle best practices, and ethical ML use
• Lead client-facing discussions on AI strategy and technical implementations

• 8 years software engineering experience with strong AI/ML and intelligent systems focus
• 3 years technical leadership role building and deploying ML systems in production
• Deep Python expertise and modern AI/ML libraries (PyTorch, Tensor Flow, Hugging Face Transformers)
• LLM experience with OpenAI, Anthropic, Cohere, open source LLMs, and prompt engineering
• Vector database familiarity (Pinecone, Weaviate, FAISS) and scalable ML infrastructure
• AI system design knowledge including data engineering for ML, model evaluation, MLOps practices
• Full-stack AI integration experience in cloud-native environments, specifically AWS
• Strong communication skills and consulting mindset for client-facing AI strategy discussions
• Innovation passion for experimentation and shaping the future of applied AI

• Advanced degree in Computer Science, AI/ML, or related technical field
• Multi-modal AI experience combining vision, language, and reasoning capabilities
• Enterprise AI deployment experience with scalability, security, and compliance requirements
• Research background with publications in AI/ML conferences or journals
• Domain expertise in specific verticals (healthcare, finance, retail, etc.)
• Open source contributions to AI/ML frameworks or communities

• Remote-first consulting environment with collaborative, innovation-focused culture
• Cutting-edge technology exposure with access to latest AI tools and platforms
• Client variety across industries and use cases, from startups to Fortune 500
• Professional development opportunities and conference attendance support
• Technical leadership path with mentoring and architectural decision-making responsibilities