Senior AI Engineer​ with Gen AI & Agentic AI

1 view
Skip to first unread message

Varun Tej Beesukuntla

unread,
Nov 10, 2025, 2:29:08 PM (2 days ago) Nov 10
to IT Recruiting
​Hi Folks,

Hope you are doing well.

This is #Varun. We have an immediate opportunity with one of our clients. Please find the job descriptions below, and if you are interested, please forward your updated resume to #varu...@interaslabs.com


​R​ole: ​Senior AI Engineer​ with Gen AI & Agentic AI

Location: R​emote

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.​

Required ​Skills:

  • ​1​3+ years of experience in data analytics and AI solutioning, with ​​5+ 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).

Reply all
Reply to author
Forward
0 new messages