Position: AI/ML (Gen AI)

Purpose of the Position:

The purpose of the AI/ML (Generative AI) role is to design, build, deploy, and operate production-grade AI systems with a strong focus on large language models (LLMs), generative AI applications, and intelligent automation.

This is a senior individual contributor role with end-to-end technical ownership and decision-making responsibility for enterprise-scale GenAI solutions. The role goes beyond model development and involves ownership of solution architecture, platform strategy, governance, and enterprise integration. The incumbent is expected to drive architectural decisions, define technical standards, evaluate trade-offs, and ensure GenAI solutions deliver measurable business outcomes while meeting scalability, security, and reliability requirements.

The AI/ML (Gen AI) acts as a technical authority and advisor, working closely with stakeholders, clients, platform teams, and delivery teams to translate complex business problems into impactful AI-driven solutions. The role also includes mentoring engineers, shaping GenAI best practices, and influencing adoption across the organization while adhering to responsible AI and governance standards. InfoCepts is a global leader of end-to-end data and analytics solutions with nearly 20 years experience enabling customers to derive value from a variety of data-driven capabilities. Unique among its peers, InfoCepts operates with the scale of a global consulting firm, yet the expertise of a niche partner.

About InfoCepts

At InfoCepts, you ll be challenged to think innovatively, while growing your own personal and professional skills designed with the future in mind. We have more than 1200 global professionals working on cutting edge technology solutions with a single mission - transforming our customers journey with data-driven modernization.

- InfoCepts has been recognized as Gartner Peer Insights Customers Choice for two consecutive years in 2020 and 2021 which recognizes our best-in-class services that help our customers approach any data analytics problem.
- We are certified by Great Place to Work , India in 2021 and recognizes our high-trust and high-performance work culture, and excellent employee experience in the industry.
- Our award-winning reusable solutions approach is well recognized in the DA industry and lets our associates leverage our collective and proven consultative expertise, accelerate solution delivery through automation, enable faster time to value with reusable toolkits - all while delivering exceptional customer experience.

Our success has been unique, and we are looking for professionals who are enthusiastic and passionate about data analytics, delivering differentiated experiences, and solving real world problems for our global customers. This position works with the competency and delivery team to execute on the assigned responsibilities.

Key Result Areas (KRAs):

1.



Technical Leadership Architecture Ownership

- Own the end-to-end technical architecture for enterprise GenAI, LLM, RAG, and LLMOps solutions.
- Drive architectural decisions including model selection, deployment approaches, build-vs-buy evaluation, and platform strategy.
- Review, validate, and approve solution designs, codebases, prompts, and evaluation frameworks.
- Define reference architectures, reusable patterns, and engineering standards for GenAI implementations across teams.

1. Enterprise GenAI Solution Delivery

- Design, own, and deliver production-grade generative AI systems using state-of-the-art techniques.
- Ensure solutions meet performance, scalability, cost-efficiency, security, and business impact expectations.
- Optimize models and pipelines for accuracy, latency, reliability, and enterprise-scale deployment.

1. LLM Application Development

- Design and implement LLM-driven applications using foundation models and APIs.
- Own prompt engineering strategies, system prompts, evaluation pipelines, and inference optimization.
- Optimize solution cost, latency, and quality across environments.

1. Retrieval-Augmented Generation (RAG)

- Architect and build RAG pipelines integrating enterprise knowledge sources with LLMs.
- Work with vector databases, embedding models, and semantic search solutions.
- Define strategies to evaluate, monitor, and reduce hallucination risks.

1. AI Platformization LLMOps

- Operationalize GenAI systems using CI/CD pipelines and MLOps/LLMOps best practices.
- Own monitoring for performance, drift, hallucinations, cost, and reliability.
- Implement versioning, rollback, observability, and controlled rollouts for GenAI solutions.

1. Stakeholder Business Advisory

- Act as a trusted technical advisor to business, leadership, and client stakeholders for GenAI initiatives.
- Translate business problems into GenAI solution strategies and technical roadmaps.
- Communicate technical trade-offs, risks, feasibility, and ROI considerations effectively to decision-makers.

1. Mentorship Capability Building

- Mentor and guide junior AI/ML engineers and data scientists.
- Conduct design, code, and prompt reviews to maintain high-quality engineering standards.
- Contribute to building organizational GenAI capability through documentation, best practices, and knowledge-sharing initiatives

1. Governance, Security Responsible AI

- Own and enforce Responsible AI, data privacy, and security standards for GenAI solutions.




- Design and implement safeguards to mitigate hallucinations, bias, misuse, and data leakage.
- Ensure solutions comply with enterprise policies, industry regulations, and ethical AI principles.

Essential Skills:

- Strong proficiency in Python with hands-on experience using PyTorch, TensorFlow, Keras, and related AI/ML frameworks.
- Deep expertise in deep learning techniques including transformer-based architectures, GANs, and neural networks.
- Experience training, fine-tuning, and evaluating large-scale AI and GenAI models.
- Strong understanding of LLMs, APIs, context management, token optimization, and enterprise integration.
- Hands-on experience designing and deploying RAG architectures using vector databases and embeddings.
- Strong software engineering skills with experience building scalable APIs and services.
- Solid understanding of MLOps and LLMOps practices including CI/CD, monitoring, observability, and cost management.
- Ability to evaluate, select, and define appropriate models, tools, and architectures based on business needs, cost, performance, and risk.
- Solid analytical and problem-solving skills with ownership-driven decision-making.

Desirable Skills:

- Experience deploying AI workloads on cloud platforms such as AWS, Azure, or GCP.
- Working knowledge of NLP techniques including text classification, summarization, and conversational AI.
- Exposure to agentic AI frameworks such as LangChain, LangGraph, CrewAI, or Semantic Kernel.
- Experience with FastAPI or Flask for serving AI models.
- Familiarity with Docker and Kubernetes for scalable deployments.
- Exposure to cloud-native GenAI services such as Azure AI Foundry, AWS Bedrock, or Vertex AI.

Qualifications:

- Education: Bachelor s or Master s degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field.
- Certifications (Preferred): Relevant certifications in AI/ML or cloud platforms (e.g., TensorFlow Developer, AWS/Azure ML certifications).
- Experience:6-9 years of experience in AI and machine learning, with demonstrated ownership of enterprise-scale generative AI solutions.

Qualities:

- Demonstrates technical leadership, ownership mindset, and the ability to influence decisions without formal authority.
- Approaches problems logically and systematically with persistence and accountability.
- Able to consult, document, and present technical decisions persuasively.
- Comfortable working in self-organized, cross-functional, and client-facing environments.
- Adapts quickly based on feedback, peer reviews, and evolving requirements
- Strong communication skills with high proficiency in written and spoken English.

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

📌 AIML Engineer (Gen AI Focused) (Bengaluru)
🏢 InfoCepts
📍 Bengaluru