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Fluency in English is a must.

We are seeking a highly skilled and visionary AI/ML Engineer to join our dynamic Sales - Gen AI Team. This is not just a development role; you will be a key player in the innovation lifecycle, from ideation to deployment. You will be responsible for designing, prototyping, and building production-grade Generative and Agentic AI solutions for a diverse range of enterprise customers.

You will leverage the latest in Large Language Models (LLMs), advanced Retrieval-Augmented Generation (RAG) techniques, and cutting-edge Agentic AI frameworks. The ideal candidate is a seasoned Machine Learning professional who combines a deep understanding of AI/ML theory with hands-on engineering prowess, a passion for solving real-world problems, and the ability to translate ambiguous business needs into concrete, scalable AI-powered systems.

Key Responsibilities:

• Solution Architecture & Development: Architect, build, and deploy robust, scalable, and intelligent solutions using LLMs and Agentic AI frameworks (LangGraph, Crew AI, Autogen, etc.).
• Customer Collaboration: Partner with the Sales and Solution Architecture teams to engage with clients, understand their business challenges, and design custom AI solutions and proof-of-concepts (PoCs).
• Advanced RAG Implementation: Design and implement sophisticated RAG pipelines, incorporating advanced techniques like query transformation, reranking, and hybrid search to ensure highly accurate and contextually relevant responses.
• Backend Engineering: Develop high-performance backend services and APIs using Python frameworks like FastAPI or Flask to serve AI models and integrate them into client ecosystems.
• Prompt & Context Engineering: Master the art and science of prompt engineering to precisely control LLM behavior. Develop strategies for context engineering to provide models with the right information at the right time.
• Cloud Platform Expertise: Leverage cloud AI platforms like Google Cloud (Vertex AI, Agent Builder), Microsoft Azure (Azure AI Studio), and AWS (SageMaker, Bedrock) to build and scale solutions efficiently.
• AI-Driven Software Acceleration: Champion and implement AI-powered tools and methodologies to accelerate the internal software development lifecycle, improving code quality, and reducing time-to-market.
• Continuous Innovation: Stay at the forefront of the rapidly evolving AI landscape, evaluating new models, frameworks, and techniques to continuously enhance our solution offerings.
• Documentation & Best Practices: Create clear, comprehensive documentation for architectures, model behaviors, and design decisions for both technical and non-technical stakeholders.

Required Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related field.
• 3 to 7 years of professional experience in a software engineering or machine learning role.
• Strong Python Proficiency: Demonstrable expertise in writing clean, efficient, and scalable Python code, including experience with backend development (FastAPI, Flask, or similar).
• Core ML/DL Expertise: Expertise in the machine learning and deep learning lifecycle, including data preprocessing, model training, fine-tuning, and optimization. Deep understanding of foundational architectures, particularly Transformers, and their applications. High proficiency with the Python data science stack (Pandas, NumPy, Scikit-learn, Matplotlib) and major deep learning frameworks (TensorFlow, PyTorch, JAX).
• Hands-on LLM Experience: Proven experience working with various LLMs (e.g., GPT series, LLaMA, Claude, Mistral, Gemini) via APIs and open-source libraries (Hugging Face Transformers, LangChain, LlamaIndex).
• Agentic AI Expertise: Practical experience building multi-step, tool-using AI agents or multi-agent systems using frameworks like LangGraph, Crew AI, or similar. This is a key requirement.
• RAG Mastery: Deep understanding and implementation experience with Retrieval-Augmented Generation (RAG) patterns and familiarity with vector databases (e.g., Pinecone, Weaviate, ChromaDB).
• Prompt Engineering Excellence: Demonstrable skill in crafting, testing, and optimizing complex prompts, including techniques like chain-of-thought, few-shot prompting, and system message design.
• Solid Foundation: Strong grasp of fundamental machine learning concepts, natural language processing (NLP), and software engineering principles (e.g., data structures, algorithms, APIs).
• Excellent Communication: Outstanding verbal and written communication skills, with the ability to articulate complex technical concepts to diverse audiences, including clients and executives.

Preferred Qualifications:

• Experience in a client-facing or consulting role, translating business requirements into technical solutions.
• Hands-on experience with LLM fine-tuning (e.g., PEFT) or Reinforcement Learning from Human Feedback (RLHF).
• Deep familiarity with at least one major cloud platform's AI stack (GCP Vertex AI, Azure AI, or AWS AI/ML services).
• Experience with MLOps practices, including containerization (Docker, Kubernetes), CI/CD pipelines, and model monitoring.
• Knowledge of Context Engineering principles and techniques.
• Official certifications in Generative AI or cloud AI platforms (e.g., Google Cloud Certified Professional - Machine Learning Engineer, Microsoft Certified: Azure AI Engineer).
• Publications in relevant AI/ML conferences or significant contributions to open-source projects are a major plus.

Why join our client's team?

• Impactful Work: Build solutions that solve real-world problems for leading global enterprises.
• Cutting-Edge Technology: Work at the absolute forefront of AI with access to the latest models, frameworks, and tools.
• Growth & Learning: Be part of a culture that fosters continuous learning, experimentation, and professional development.
• Collaborative Environment: Join a brilliant and passionate team of engineers, data scientists, and business leaders dedicated to pushing the boundaries of what's possible with AI.

CKCODECONNECT is an Equal Opportunity Employer and does not discriminate based on race, age, color, religion, sex, sexual orientation, gender identity, national origin, veteran, disability status or any other characteristic protected by applicable law.