Role: Senior AI Engineer with Gen AI & Agentic AI

Location: Remote

Duration: Long Term

Must have 15+ years of experience

Note: Only GC & USC candidates with PP number and copy

Overview:

We are seeking a highly skilled Senior AI Engineer to design, develop, and deploy intelligent, scalable, and secure AI solutions. The ideal candidate has a deep understanding of Generative AI, Agentic AI, and Large Language Models (LLMs), along with a proven ability to translate business requirements into advanced AI-driven architectures and applications.

You will work closely with cross-functional teams to design end-to-end AI/ML systems, leveraging cloud platforms, modern data stacks, and MLOps frameworks to deliver measurable business impact.

Key Responsibilities:

• Architect and implement advanced AI/ML and Generative AI solutions aligned with business goals.
• Collaborate with business and technical stakeholders to identify AI opportunities, define requirements, and ensure successful delivery.
• Develop and fine-tune LLMs (OpenAI, Anthropic, Mistral, LLaMA, etc.) using frameworks like LangChain, CrewAI, or AutoGen.
• Build and orchestrate intelligent multi-agent systems and workflow automation pipelines.
• Integrate AI solutions within cloud environments (AWS, Azure, GCP) and data ecosystems (Snowflake, Databricks, Airflow, dbt).
• Apply best practices in data governance, model performance, scalability, and security.
• Leverage Python and industry-standard AI/ML libraries (e.g., Hugging Face, OpenAI SDKs) for experimentation and deployment.
• Drive continuous improvements through MLOps, CI/CD, and monitoring strategies.
• Present technical concepts and business outcomes to executive and client stakeholders.

Required Skills:

• 15+ years of experience in data analytics and AI solutioning, with 10+ years focused on Generative AI and Agentic AI.
• Strong hands-on experience in AI/ML, NLP, LLMs, and AI orchestration tools.
• Proven success in client-facing consulting roles, leading business discovery and solution delivery.
• Expertise in cloud ecosystems (AWS, Azure, or GCP) and modern data stack tools (Snowflake, Databricks, Airflow, dbt).
• Proficiency in Python and libraries like Hugging Face, LangChain, and OpenAI SDKs.
• Solid understanding of solution architecture, security, integration patterns, and scalability best practices.
• Excellent communication, presentation, and stakeholder management skills.

Preferred Qualifications:

• Experience with AI agent frameworks (CrewAI, AutoGen, LangGraph, LangChain, Strands).
• Familiarity with MLOps tools and practices (SageMaker, MLflow, Vertex AI, Azure ML).
• Exposure to regulated domains such as finance, healthcare, or insurance.
• Certifications in cloud, AI/ML, or data engineering (e.g., AWS ML Specialty, Azure AI Engineer).