Job
Description
Key Responsibilities: AI/ML Architecture & Development Architect and implement end-to-end AI/ML solutions using Gen AI and LLMs tailored to business use cases. Design, fine-tune, and deploy large language models such as OpenAI GPT-4o, Gemini, Claude, LLaMA 3.2, and Phi. Build and scale production-ready applications using frameworks like FastAPI, Django, or similar. Develop, maintain, and optimize MLOps pipelines for automated model training, deployment, monitoring, and governance. Generative AI & NLP Expertise Lead the development and integration of generative AI models for applications including summarization, Q&A, sentiment analysis, and translation. Apply NLP and deep learning to enhance performance and reliability of models for complex user interactions. Engage in prompt engineering, vector DB integration, and fine-tuning using Azure OpenAI Service or equivalent platforms on AWS/GCP. System Design & Integration Collaborate closely with data engineering teams to build and manage scalable, cloud-native solutions. Design and deploy event-driven architectures and real-time data processing systems. Work with microservice architectures, containerization tools (Kubernetes, Docker), and cloud platforms (Azure/AWS/GCP). Frameworks & Tooling Use advanced frameworks like LangChain, LlamaIndex, Semantic Kernel, and AutoGen to build scalable LLM applications. Work extensively with data processing tools such as Apache Spark, TensorFlow, PyTorch, Pandas, and Scikit-learn. Technical Leadership Lead cross-functional AI teams and mentor junior engineers and data scientists. Establish and enforce development standards, best practices, and code quality benchmarks. Stay up-to-date with research and contribute to open-source initiatives where applicable. Project & Stakeholder Management Interface with business stakeholders to understand requirements, define AI/ML strategies, and deliver impactful solutions. Handle multiple engagements simultaneously while ensuring timely and high-quality project delivery. Support pre-sales and solutioning efforts including RFPs, RFIs, and client presentations. Required Qualifications: Proven expertise in designing and implementing LLM-based and Gen AI solutions. Hands-on experience with OpenAI, Claude, Gemini, LLaMA 3.2, Phi, and other foundational/open-source models. Strong command over NLP, deep learning, predictive analytics, and data modeling. Proficiency in cloud platforms (Azure preferred; AWS/GCP also acceptable), especially cloud-native and AI tools. Experience with distributed systems, APIs, event-driven architecture, and real-time data streaming. Solid experience with DevOps tools including Azure DevOps, MLflow, or other MLOps platforms. Strong understanding of user interaction patterns with large datasets and search systems. Knowledge of vector databases and semantic search (e.g., Pinecone, FAISS, Weaviate, etc.). Preferred Attributes: Demonstrated success leading AI projects from conception to deployment. Strong business acumen with ability to map AI solutions to business needs. Excellent problem-solving, communication, and collaboration skills. Experience working in Agile environments and managing multi-disciplinary teams.
