Gen AI Engineer
Indexed description
In the assigned Job Role of Data Science Consultant 2, your Area Of Responsibility will be as below:
- Develop data preparation tasks, while identifying patterns or anomalies.
- Ensure data readiness for advanced modeling.
- Develop models for complex use cases (e.g., forecasting models, LLM-based solutions), while refining algorithms to meet business needs, and ensure smooth deployment into scalable, production-ready solutions.
- Conduct testing and optimize algorithms for performance, reliability, and scalability, while providing guidance to team members in best practices.
- Design and develop predictive models and data-driven analyses to address business challenges.
- Build, evaluate, and deploy models, standardize code, and contribute to knowledge management.
- 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.
- Define analytics problems for projects; execute visualization, analysis, and predictive modeling under guidance.
- Proactively maintain models and implement improvements for accuracy and reliability.
- Apply governance controls to mitigate risks and ensure compliance.
- Analyze performance trends, recommend improvements, and document discrepancies for escalation.
- Maintain comprehensive documentation standards, while participating in knowledge transfer sessions.
- Participate in discussions with stakeholders to refine requirements, provide insights, and guide implementation of models.
- Apply the predefined quality measurement framework at an individual task level in the project.
- Deploy complex analytics tools or multi-system integration, while validating deployment success.
- Participate in developing scripts or templates for repeated deployments tasks.
- Contribute to analytic solutions, IP asset creation, and training initiatives.
- Contribute to thought leadership such as papers, innovative non-ML, ML, deep learning or LLM models, and proofs of concepts.
- Participate in and deliver analytics training, while contributing to content creation.
- Provide input for segment and unit-level business plans.
- Deliver scalable, high-quality analytics solutions aligned to business needs.
- A knack for optimization, deployment and performance improvement of models.
- The ability to drive innovation through advanced analytics, automation and thought leadership.
- Enable team growth through knowledge sharing, training and standardization.
- Support business planning with data-driven insights.
- Python and hands-on building of enterprise GenAI applications with Lang Chain, Lang Graph, Llama Index, or similar orchestration frameworks; comfortable with RAG, vector databases, agentic workflows (tool calling, memory, multi-agent), and prompt engineering.
- Working with Azure OpenAI, AWS Bedrock, OpenAI, Anthropic, or similar LLM platforms; integrating with enterprise APIs, databases, and knowledge repositories.
- Building production APIs and microservices with Fast API, Docker, and Kubernetes; software engineering fundamentals (system design, testing, CI/CD, Git); hands-on with AI coding assistants (GitHub Copilot, Claude Code, Cursor) for engineering productivity.
- LLMOps practices — observability, tracing, evaluation (RAGAS, DeepEval, Lang Smith), guardrails, cost governance, and model safety.
- conducting code reviews, driving technical decisions, and collaborating with product and platform teams.
- Open-source LLMs (Llama, Mistral, Gemma) and fine-tuning techniques (LoRA, QLoRA, PEFT); familiarity with Model Context Protocol (MCP).
- Multimodal AI (vision-language, OCR, speech) and document intelligence.
- Front-end (React, TypeScript), DevOps/IaC tooling (GitHub Actions, Terraform, Helm), and domain exposure across financial services, telecom, retail, or healthcare
- 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.
- 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
EEO
Infosys provides equal employment opportunities to applicants and employees without regard to race; color; sex; gender identity; sexual orientation; religious practices and observances; national origin; pregnancy, childbirth, or related medical conditions; status as a protected veteran or spouse/family member of a protected veteran; or disability.
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