Gen AI LLMOps Engineer
Responsibilities
LLM Deployment & Productionization
Deploy and manage LLMs (OpenAI, Llama, Mistral, etc.) in production environments
Build scalable inference pipelines (real-time & batch)
Integrate LLMs into applications via APIs and microservices
LLMOps / GenAI Pipeline Development
Design and implement end-to-end LLM pipelines:
Prompt engineering
Retrieval-Augmented Generation (RAG)
Fine-tuning / embeddings
Work with frameworks like:
LangChain, LangGraph, LlamaIndex
RAG & Data Integration
Build and optimize RAG pipelines using vector databases
Work with tools like:
Pinecone, FAISS, Weaviate, Chroma
Handle document ingestion, chunking, indexing, and retrieval
Model Monitoring & Optimization
Monitor LLM performance:
Latency
Accuracy / hallucinations
Cost efficiency
Implement:
Prompt optimization
Feedback loops
Guardrails & evaluation frameworks
MLOps for LLMs
Build CI/CD pipelines for:
Model updates
Prompt/version control
Manage experiment tracking and deployments
Ensure reproducibility of LLM workflows
Additional Responsibilities
What This Role Is NOT
❌ Not pure:
Data Scientist (model building only)
Platform Engineer (infra-heavy role)
Traditional MLOps without LLM exposure
✅ This role focuses on:
LLM deployment + RAG + GenAI pipelines
Operationalizing GenAI applications
Technical and Professional Requirements
Strong Python programming
Hands-on experience with LLMs / Generative AI
Experience with:
LangChain / LangGraph / LlamaIndex
Solid understanding of:
RAG architecture
Prompt engineering
Embeddings & vector search
Experience building APIs using:
FastAPI / Flask
Preferred Skills
- Generative AI for Data Analytics
Educational Requirements
MCA,MSc,MTech,Bachelor of Engineering,BCA,BSc,BTech
RPA-GenAI Trust and Assurance Consultant
Responsibilities
- Define and execute testing strategies for Generative AI/LLM systems, covering functional, non-functional, and safety-focused validation.
- Design evaluation frameworks and test suites using tools such as DeepEval to measure quality, robustness, and consistency of model outputs.
- Plan and conduct red teaming exercises to identify vulnerabilities (e.g., prompt injection, jailbreaks, harmful content, data leakage) and recommend mitigations.
- Establish Responsible AI assurance checks aligned to fairness, transparency, privacy, and safety expectations.
- Create clear test plans, evidence, dashboards, and reports that communicate risks, findings, and remediation priorities to stakeholders.
- Collaborate with engineering and product teams to integrate AI testing into delivery pipelines and improve release readiness criteria.
- Support incident triage and root-cause analysis for model behavior issues, regressions, and evaluation drift across versions.
Additional Responsibilities
- Proven experience executing red teaming for LLM applications and translating findings into actionable controls and mitigations.
- Practical experience implementing Responsible AI practices and assurance workflows across the AI lifecycle.
- Strong understanding of LLM failure modes (hallucinations, toxicity, bias, prompt sensitivity) and methods to test and reduce them.
- Experience building automated evaluation pipelines and regression suites for LLM systems using DeepEval or similar frameworks.
- Consulting experience: stakeholder management, requirement discovery, and delivering clear outcomes under ambiguity.
Technical and Professional Requirements
- BTech/BE or equivalent technical degree.
- 3–9 years of experience in testing/quality engineering, with hands-on exposure to Generative AI or LLM testing initiatives.
- Working knowledge of AI testing concepts, including test design, evaluation metrics, and result interpretation for LLM outputs.
- Experience contributing to structured documentation such as test plans, test evidence, and defect/risk reporting.
Preferred Skills
- Generative AI – Basic
- Prompt Engineering
- Responsible AI
- Agent Engineering
- LLMOps
- Testing
- Machine Learning
Educational Requirements
Bachelor of Engineering
Power Programmer – Senior Technologist Python Engineer- Regular(Q1-FY-26)
Responsibilities
Power Programmer is an important initiative within Global Delivery to develop a team of Full Stack Developers who will be working on complex engineering projects, platforms and marketplaces for our clients using emerging technologies.,
- They will be ahead of the technology curve and will be constantly enabled and trained to be Polyglots.,
- They are Go-Getters with a drive to solve end customer challenges and will spend most of their time in designing and coding, End to End contribution to technology oriented development projects.,
- Providing solutions with minimum system requirements and in Agile Mode.,
- Collaborate with Power Programmers.,
- Open Source community and Tech User group.,
- Custom Development of new Platforms & Solutions ,Opportunities.,
- Work on Large Scale Digital Platforms and marketplaces.,
- Work on Complex Engineering Projects using cloud native architecture .,
- Work with innovative Fortune 500 companies in cutting edge technologies.,
- Co creates and develop New Products and Platforms for our clients.,
- Contribute to Open Source and continuously upskill in latest technology areas.,
- Incubating tech user group
Technical and Professional Requirements
Python
Preferred Skills
- PYTHON
- Python – Big Data
- Django
Educational Requirements
Bachelor of Engineering
Senior Technologist – AI/GenAI-Q1-2026(Regular)
Responsibilities
# AI/GenAI Application Development and deployment
# Model Implementation, fine-tuning, and optimization
# Technical Innovation and emerging technology evaluation
# Production AI System Deployment and maintenance
# Elaborate Technical Documentation and knowledge sharing
# Cross-functional Collaboration with data science and product teams
# Research & Development of cutting-edge AI capabilities
# Problem Solving for complex production AI issues
Additional Responsibilities
# 2+ years GenAI/LLM hands-on experience (critical differentiator)
# Production AI system deployment experience
# Understanding of AI ethics and responsible AI practices
# Data visualization and analytics capabilities
Technical and Professional Requirements
# Deep Programming Skills: Python, Java, SpringBoot, SQLbr
# AI/ML Frameworks: PyTorch, TensorFlow, Scikit-learn (hands-on coding)
# GenAI Agentic Application design, Implementation
# Production ML model deployment and monitoring
# Real-time inference systems and distributed computing
# API design and microservices architecture
# Data pipeline architecture and stream processing
# MLOPs/LLMOps exposure
Preferred Skills
- AgentOps
- Artificial Intelligence – ALL
- OpenSource Database
- Agent Engineering
- IOT Analytics – Machine Learning
- MLOps
- LAMP stack
- SQL Server
- ACCORD
Educational Requirements
Bachelor of Engineering
Director – Data Engineering and AI Platforms
Responsibilities
Data Engineering & Architecture
- Serve as a hands-on technical leader in the design of scalable data pipelines, data stores, and information flows across the enterprise.
- Design and optimize cloud-based big data platforms, including ingestion, transformation, storage, and consumption layers.
- Lead the engineering of ETL/ELT frameworks, streaming pipelines, and batch processing solutions.
- Conduct enterprise-wide assessments of data stores and data flows to identify bottlenecks, friction points, and modernization opportunities.
- Own data modeling standards to ensure alignment with business objectives, performance, and accessibility.
AI Enablement & Advanced Analytics
- Enable and support AI/ML and GenAI initiatives by building reliable, high-quality, and well-governed data pipelines.
- Collaborate with Data Science teams to operationalize models, including feature engineering pipelines, inference data flows, and model monitoring data.
- Support AI-driven use cases such as predictive analytics, recommendations, NLP-based insights, and intelligent automation.
- Stay current with market trends, embed innovative practices into strategy, and drive the organization forward with an AI-first approach — ensuring AI initiatives move beyond proof-of-concept to enterprise-scale solutions.
- Approach data engineering with an AI mindset and vice versa, reflecting the evolving and inseparable nature of the two disciplines.
Technical and Professional Requirements
Desired Qualifications
- Experience in financial services, with understanding of consumer and commercial banking data.
- Experience supporting or enabling AI/ML and GenAI solutions, including feature pipelines and analytics platforms.
- Familiarity with data visualization and BI tools (Tableau, Cognos, SAS).
- Knowledge of responsible AI, data governance, and regulatory considerations in highly regulated environments.
- Experience modernizing legacy data platforms into cloud-native architectures.
- Executive speaking skills — ability to articulate strategy, challenge the status quo, and present to senior leadership and key stakeholders with confidence.
- Experience working across or within highly collaborative, non-hierarchical organizational cultures with an emphasis on peer relationships and open communication.
Preferred Skills
- LLMOps
- Artificial Intelligence – ALL
- Databricks
- Generative AI – Basic
Educational Requirements
Bachelor of Engineering
Principal Technologist – Software Engineering
Responsibilities
Key Responsibilities
- Define and execute the technology strategy across risk, governance, regulatory, policy, and enterprise oversight platforms.
- Provide overall leadership and accountability for a portfolio of applications, data platforms, and analytics capabilities, ensuring reliability, scalability, and security.
- Oversee the design, development, and operational management of modern data pipelines and data products, ensuring high standards for data quality, integrity, and security.
- Partner with data scientists, analysts, and platform teams to identify and implement data-driven and AI-enabled solutions that address complex business and risk challenges.
- Act as a strategic technology partner to senior executives, contributing to ideation, innovation, prioritization, and long-term strategic alignment.
- Build and maintain multi-year business and technology roadmaps, and ensure the successful delivery of aligned initiatives.
- Lead resource strategy, staffing, and capacity planning across delivery and support teams (FTEs and contractors) to ensure effective execution and platform stability.
- Partner closely with enterprise architecture, infrastructure, and shared technology services to ensure solutions align with enterprise standards and long-term strategy.
Technical and Professional Requirements
Key Responsibilities Continued ::
- Serve as an experienced product or experience owner, helping shape priorities and drive value-focused delivery.
- Manage third-party vendor engagements, including scope definition, contract terms, delivery performance, and financial management.
- Research and evaluate emerging AI and ML technologies, identifying opportunities to improve analytical capabilities, insights, and operational outcomes.
- Oversee the development and deployment of AI/ML models supporting monitoring, risk assessment, analytics, and reporting use cases.
- Ensure that all platforms and solutions meet enterprise standards for governance, controls, auditability, and regulatory expectations.
- Work effectively within a matrix organisation — collaborating across core engineering teams, business leadership, and peers across geographies, balancing both leadership and service capabilities.
Preferred Skills
- Artificial Intelligence – ALL
- PYTHON
Educational Requirements
Bachelor of Engineering
Distinguished Architect – AI/GenAI
Responsibilities
The Distinguished Architect will be responsible for:
- Leading a team of architects; offering guidance, thought leadership and ensuring proper resource allocation in order to deliver top-quality solutions.
- Developing architectural strategy across assigned Company Platforms, ensuring enterprise-level consistency and alignment.
- Establishing and communicating strategy to executive staff, industry partners and customers; using recognized technical and business expertise to influence, guide, and craft business strategy and decision-making at the highest interpersonal levels.
- Providing consultation, design input, technical direction and feedback for consistent Company Platform architectural approaches across portfolio Principal Architects and senior engineering leadership.
- Driving and developing product and solution strategies that inform product requirements and investment decisions for Company Platforms across the organization, weaving the enterprise technology vision into the planning and investment processes.
- Implementing robust controls, governance, and risk management for AI platforms, including data security, privacy, and continuous monitoring, with reference to current and future toolsets and platform capabilities.
- Ensuring platform controls and governance are integrated with durable enterprise architecture principles, enforcing resilience, observability, and compliance across all AI initiatives.
Preferred Skills
- Architecture – ALL
- Azure Development & Solution Architecting
- retrieval augmented generation (rag)
Educational Requirements
Bachelor of Engineering
Solution Architect – AI & Mfg Intelligence
Job Description
This role involves the development and application of engineering practice and knowledge in defining, configuring and deploying industrial digital technologies (including but not limited to PLM and MES) for managing continuity of information across the engineering enterprise, including design, industrialization, manufacturing and supply chain, and for managing the manufacturing data.
Job Description – Grade Specific
Focus on Digital Continuity and Manufacturing. Establishes trust and credibilty with customer accounts. Shows clear dedication and commitment to business objectives. Operates with no supervision in complex environments. Sets and manages realistic and deliverable expectations. Considers ˜the bigger picture when making decisions. Motivates the team by generating a positive and enthusiastic atmosphere.
Solution Architect – Process Industry
Job Description
This role involves the development and application of engineering practice and knowledge in defining, configuring and deploying industrial digital technologies (including but not limited to PLM and MES) for managing continuity of information across the engineering enterprise, including design, industrialization, manufacturing and supply chain, and for managing the manufacturing data.
Job Description – Grade Specific
Focus on Digital Continuity and Manufacturing. Establishes trust and credibilty with customer accounts. Shows clear dedication and commitment to business objectives. Operates with no supervision in complex environments. Sets and manages realistic and deliverable expectations. Considers ˜the bigger picture when making decisions. Motivates the team by generating a positive and enthusiastic atmosphere.
MES Solution Architect (Siemens Opcenter)
Job Description
This role involves the development and application of engineering practice and knowledge in defining, configuring and deploying industrial digital technologies (including but not limited to PLM and MES) for managing continuity of information across the engineering enterprise, including design, industrialization, manufacturing and supply chain, and for managing the manufacturing data.
Job Description – Grade Specific
Focus on Digital Continuity and Manufacturing. Fully competent in own area. Acts as a key contributor in a more complexor critical environment. Proactively acts to understand and anticipates client needs. Manages costs and profitability for a work area. Manages own agenda to meet agreed targets. Develop plans for projects in own area. Looks beyond the immediate problem to the wider implications. Acts as a facilitator, coach and moves teams forward.