45 applicants

Company

EXL · 18 hours ago

Solutions AI Architect

United States

Full-time

Remote

Mid, Senior Level

$180K/yr - $220K/yr

2+ years exp

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Hiring Manager

Abhisha Bankawat

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Responsibilities

Ensure success in designing, building and deploying applications, software, and services on the EXL AI platform.

Interact with customers directly to understand the business problem, help and aid them in implementation of their ML ecosystem

Educate customers on the value proposition of EXL and showcase the art of possible.

Participate in deep architectural discussions and design exercises to create world-class solutions built on our clients stack and/or EXL while ensuring solutions are designed for successful deployment in the cloud.

Author and contribute to EXL customer-facing publications such as whitepapers, workshops, demos and proof of concepts.

Build deep relationships with senior technical individuals within customers to enable them to be AI advocates.

Capture and share best-practice knowledge amongst the EXL AI solutions architect community.

Design generative AI solutions leveraging state-of-the-art models (e.g., GPT4o1, Claude, Llama3.1) to meet client-specific business objectives.

Translate business requirements into AI architectures, frameworks, and roadmaps.

Develop domain-specific strategies for implementing generative AI within industries such as insurance, healthcare, and banking.

Guide technical teams in building, fine-tuning, and deploying large language models (LLMs) and multimodal AI solutions.

Architect scalable, secure, and maintainable AI pipelines on cloud platforms like AWS, Azure, or GCP.

Stay current on advancements in generative AI, NLP, and machine learning frameworks (e.g., TensorFlow, PyTorch, LangChain, LlamaIndex, LangGraph, Crew.ai, Autogen).

Collaborate with clients to identify opportunities for AI-driven transformation and innovation.

Present generative AI use cases, proofs of concept, and success stories to both technical and non-technical audiences.

Act as a trusted advisor to clients on the ethical, technical, and operational considerations of implementing generative AI.

Lead client solutioning during the client 1st engagement to understand the client’s needs, as part of go-to-market and/or lead the end-to-end Proof of Concept delivery of generative AI projects, from ideation to production deployment.

Ensure solutions meet compliance, security, and scalability standards.

Provide post-implementation support and optimization recommendations.

Qualification

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Generative AILarge Language ModelsPythonDeep Learning FrameworksAI Architecture DesignML EngineeringMLOpsNLPCloud ServicesPrompt EngineeringAI GovernanceStatistical ConceptsGraph DatabaseVector DatabaseVersion ControlAI Model DeploymentRFI/RFP Participation

Required

Masters of Science or PhD in computer science, data science, statistics, Natural Language Processing

2-3 years of experience in GenAI and Large Language Models.

Hands-on experience with current deep learning frameworks (e.g., PyTorch, TensorFlow) as evidenced by released code (e.g., GitHub repositories – version control awareness).

Solid understanding of optimization techniques for training deep neural networks, regularization methods, and hyperparameter/fine tuning.

Experience in Generative AI Models and LLMs, finetuning LLMs, prompt engineering and experience with LLM orchestration frameworks like Langchain, LlamaIndex, RAGAS, etc.

Strong software engineering skills for rapid and accurate development of AI models and systems.

Understanding of Agentic AI, Autonomous Agents, AI Agents, AutoGen, Crew.ai, Langchain, and workflow steps design. NVIDIA Blueprints. Google AI Agents.

Provide business-oriented solution with ability to communicate effectively, both verbally and in writing, with technical and non-technical stakeholders.

Experience working in a collaborative environment, contributing to multidisciplinary teams and projects.

Proven ability to solve complex problems, think creatively, and adapt to evolving research trends.

5 years of experience in AI, NLP, Computer Vision and related technologies

Excellent communication and problem-solving skills.

Working with cross-functional teams across different stakeholders.

Ability to explain GenAI to non-technical audiences across many different industries. Ability to do GenAI Architecture solutioning for existing clients and potential clients.

People leadership skills. Candidate is also hands on developer while people managing Data Scientists, ML Engineers etc.

Experience in ML Engineering and MLOps, MLFlow

Strong understanding of statistical and machine learning concepts

Experience with deep learning frameworks such as TensorFlow and PyTorch

Familiarity with key concepts and techniques used in generative models, such as variational autoencoders (VAEs), generative adversarial networks (GANs), and flow-based models.

Strong programming skills in languages such as Python, along with experience working with popular deep learning frameworks like PyTorch and TensorFlow.

Understanding of Graph Database and/or Vector Database along with knowledge of cloud services (e.g., AWS, Azure, GCP).

Experience with deploying AI models in production environments.

Familiarity with domain-specific applications of generative AI

Leveraged both Azure and AWS for model inferencing. For finetuning, he has worked more on AWS SageMaker.

Has used different retrieval, reranking, and generation techniques based on the use case complexity and the metrics required.

Has played multiple roles in the past, such as an individual contributor, a solution architect, a mentor, a trainer, and a people manager.

He also participates in RFI, RFP, thought leadership, and business development activities.