Infosys

Gen AI Solution Engineer

Infosys$90K — $130K *
Enterprise Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • 5-7 years of experience in data science and advanced modeling.
  • Expertise in Generative AI and associated technologies.
  • Experience with orchestration frameworks and vector databases.
  • Solid knowledge of AI governance and model safety protocols.
  • Bachelor's degree or equivalent experience required.

Responsibilities

  • Review data preparation and ensure readiness for advanced modeling.
  • Refine algorithms for complex forecasting and LLM solutions.
  • Build tailored analytics models and solutions for business needs.
  • Oversee execution of analysis to drive actionable business insights.
  • Enhance analytics with reusable customizations using tools like SAS and Python.

Benefits

  • Comprehensive medical, dental, and vision insurance.
  • Disability insurance (both long-term and short-term).
  • Health and dependent care reimbursement accounts.
  • 401(k) retirement plan with contributions.
  • Generous paid holidays and PTO allowance.
Full Job Description
Job details

Job Role

Data Science Consultant 3

Career Role

Data Scientist

Work Location

Austin, TX, Charlotte, NC, Houston, TX, Newjersey, NJ, Raleigh, NC, Richardson, TX, Sunnyvale, CA

State / Region / Province

California, New Jersey, North Carolina, Texas

Country

USA

Domain

Delivery

Interest Group

Infosys Limited

Company

ITL USA

Requisition ID

148316BR

Technical Skills 1

Technology|Generative AI|Conversational AI Platform

Technical Skills 2

Technology|Machine Learning|Generative AI

Technical Skills 3

Technology|AI Hyperscalers|Azure Agentic AI Services

Technical Skills 4

Technology|AI Hyperscalers|Google Agentic AI Services

Technical Skills 5

Technology|AI Hyperscalers|AWS Agentic AI Services

In the assigned Job Role of Data Science Consultant 3, your Area Of Responsibility will be as below:
• Review data preparation tasks, and plans to address patterns or anomalies, while ensuring data readiness for advanced modeling and AI.
• Review models for complex use cases (e.g., forecasting models, LLM-based solutions), and refine algorithms to meet business needs.
• Review plan for smooth deployment into scalable, production-ready solutions.
• Review test plans and test results for analytics use cases, while defining optimization standards for model accuracy and stability, in alignment with business goals.
• Build models and analytics solutions tailored to business needs.
• Ensure quality and scalability across client engagements while actively contributing to knowledge assets and innovation streams.
• Leverage tools like SAS and R/Python to create reusable customizations for non-ML, ML, and deep learning algorithms, while enhancing analytics including LLMs, and create innovative, cost-effective solutions.
• Review and refine analytics problems; identify data sources and extract from diverse environments.
• Oversee analysis execution and drive business insights.
• Create monitoring strategies across multiple projects, embedding governance frameworks to ensure robustness, reliability, and risk awareness.
• Review monitoring frameworks, refine documentation/reporting templates, and present insights on anomalies or slippages to stakeholders.
• Refine documentation strategy across teams, ensuring transparency and reproducibility of complex analytics solutions.
• Collaborate with cross-functional teams, ensuring alignment between analytics delivery and business strategy.
• Review analytics outputs for adherence to quality frameworks and project commitments.
• Recommend improvements to quality metrics and guide team members to align with standards.
• Identify and recommend model changes needed for successful deployment.
• Engage in creation and refinement of IP assets such as analytics prototypes and accelerators.
• Develop insights, whitepapers, and proof-of-concept summaries that highlight innovative thinking.
• Review innovative models and applications in non-ML, ML, deep learning, or LLM areas.
• Support participation in forums and internal knowledge exchanges.
• Deliver training sessions on technical and analytics-specific topics.
• Collaborate on content creation and mentor team members through hands- on guidance in live projects.
• Provide input for segment and unit-level business plans.

Your contribution to the team:
• A strong focus on innovation and scalable analytics solutions.
• Proactive problem-solving ability for complex, data-driven business challenges.
• Deep technical expertise across advanced modeling and AI use cases.
• A strategic mindset to align analytics with business goals.
• Ability to mentor team members and drive continuous improvement.
• Strong communication and knowledge-sharing capabilities.

Required Skill and Experience
• Enterprise GenAI and Agentic AI solutions across RAG, AI agents, conversational AI, enterprise search, workflow automation, document intelligence, and AI copilots; comfortable with planner-executor, reflection, multi-agent, and graph-based orchestration patterns.
• Hands-on with orchestration frameworks (LangChain, LangGraph, LlamaIndex, Semantic Kernel, AutoGen, CrewAI) and vector databases (Pinecone, Weaviate, Milvus, pgvector, FAISS, ChromaDB, Azure AI Search); working knowledge of grounding, prompt engineering, and context management.
• Experience integrating GenAI with Azure OpenAI, AWS Bedrock, Vertex AI, OpenAI, Anthropic, and Gemini, along with enterprise APIs, middleware, and data platforms.
• Command of AI governance, LLMOps, evaluation, observability, guardrails, model safety, compliance, and cloud-native deployment.
• Ability to define reference architectures, lead solutioning discussions, drive architecture reviews, and collaborate with enterprise architects, business stakeholders, and engineering teams.

Preferred Skill and Experience
• Exposure to open-source LLM ecosystems - Hugging Face, PyTorch, LoRA, QLoRA, PEFT - and models such as Llama, Mistral, Gemma, DeepSeek, and Falcon.
• Familiarity with multimodal AI, including vision-language models, speech and audio models, and image or video generation.
• Familiarity with DevOps and IaC tooling (GitHub Actions, Jenkins, Terraform, Helm, Kubernetes) and awareness of front-end stacks (React, Angular, TypeScript, GraphQL) used in copilot interfaces.

Additional Required Qualifications
• Bachelor's degree or foreign equivalent required from an accredited institution. Will also consider three years of progressive experience in the specialty in lieu of every year of education.
• This position may require relocation and/or travel to work/project location.
• Candidates authorized to work for any employer in the United States without employer-based visa sponsorship are welcome to apply. Infosys is unable to provide immigration sponsorship for this role now or in the future.

Benefits

Along with competitive pay, as a full-time Infosys employee you are also eligible for the following benefits:
  • Medical/Dental/Vision/Life Insurance
  • Long-term/Short-term Disability
  • Health and Dependent Care Reimbursement Accounts
  • Insurance (Accident, Critical Illness , Hospital Indemnity, Legal)
  • 401(k) plan and contributions dependent on salary level
  • Paid holidays plus Paid Time Off

About Infosys

Infosys Limited is an Indian multinational corporation that provides business consulting, information technology and outsourcing services. It has its headquarters in Bangalore, Karnataka, India. Infosys is the second-largest Indian IT company after Tata Consultancy Services by 2017 revenue figures and the 596th largest public company in the world based on revenue. On 31 March 2018, its market capitalisation was $37.32 billion. The credit rating of the company is A? (rating by Standard & Poor's).
Learn more about Infosys
Size
314,015 employees
Market Cap
$77.5 billion
Industry
Net Income
$178.5 billion
Founded
2004
5 Year Trend
+12.2%
Revenue
$945.9 billion
NASDAQ

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