AI Engineer

• Review and evaluate AI-generated code across programming languages and software engineering scenarios
• Assess code for correctness, reliability, security, scalability, readability, and maintainability
• Identify bugs, logical errors, incomplete implementations, edge-case failures, and architectural weaknesses
• Analyze unfamiliar codebases and understand the impact of proposed changes
• Review bug fixes, feature implementations, refactoring, API integrations, configuration changes, and database operations
• Compare alternative implementations and determine whether they satisfy technical requirements
• Rewrite or improve code to create high-quality reference solutions
• Provide clear technical explanations of identified issues and recommended improvements
• Develop evaluation criteria, technical annotations, and rubrics for code-quality assessment
• Collaborate with researchers and engineering teams to design coding benchmarks and improve LLM evaluation methodologies

Senior Software Engineer – AI Code Evaluation

• Design, develop, and maintain scalable data engineering and analytics solutions
• Build reliable data pipelines for batch and real-time processing
• Develop data platforms and workflows using Databricks and modern cloud technologies
• Work with large and complex datasets for analytics, reporting, and AI-driven applications
• Design data models and optimise processing workflows for performance and scalability
• Integrate structured and unstructured data sources
• Implement data quality, validation, monitoring, and governance practices
• Collaborate with data scientists, analysts, engineers, product teams, and business stakeholders
• Translate business requirements into scalable technical and data solutions
• Troubleshoot pipeline, processing, performance, and integration issues
• Optimise data architectures and workflows for reliability, efficiency, and cost
• Contribute to cloud-based data architecture and platform modernisation
• Develop reusable frameworks, components, and data engineering best practices
• Support deployment, monitoring, and maintenance of production data solutions
• Stay current with emerging data engineering, cloud, analytics, AI, and modern data platform technologies

Senior Gen AI Engineer

• Review proposed coding tasks and programming environments for realism
• Provide technical feedback on the structure and difficulty of evaluation harnesses
• Walk through the approach to verifying complex code challenges
• Suggest improvements to make test suites more robust
• Participate in an AI-moderated session focused on coding evaluation harnesses

Software Engineer, AI Evaluation

• Build and own the document ingestion and extraction pipeline for PDF and HTML inputs, text-layer and scanned documents, OCR fallback, and layout-aware parsing
• Design the canonical output schema and extraction logic for heterogeneous source formats
• Implement span grounding with verbatim source text and locators to the original source
• Build an evaluation harness with a labeled golden set, per-field precision and recall, and regression testing
• Calibrate confidence scoring and thresholds for automatic acceptance versus human review
• Design and build human-in-the-loop review workflows with product and design partners
• Own cost and latency per document through model tiering, caching, and batching
• Instrument the system to surface silent failures and monitor production drift and regression
• Partner with a domain expert to define taxonomy, adjudicate edge cases, and maintain labeling guidelines

Senior AI Engineer

• Provides design documents and translates them into component-level designs to accelerate development
• Provides design expertise supporting development teams with flexible, reusable components
• Analyzes, designs, and reviews applications to ensure customer specifications are satisfied
• Liaises between application architects and development teams to coordinate product development and implementation
• Develops accurate and relevant design requirements with product development teams and senior designers
• Reviews technical research and evaluates tools and methodologies against industry, client, and company standards
• Develops technical documentation and participates in test-plan development, integration, and deployment
• Participates in business process work sessions, project meetings, and joint application development sessions
• Acts as a domain expert and explains application design to software developers
• Coordinates application design activities to enhance product quality and efficiency
• Defines and develops project requirements, functional specifications, and detailed application solution designs
• Provides leadership and work guidance to less experienced personnel and developers

• Design, develop, and deploy Generative AI applications using Large Language Models and modern AI frameworks
• Build and maintain scalable backend services and REST APIs using Python frameworks such as FastAPI, Flask, or Django
• Implement RAG pipelines and semantic search solutions using vector databases
• Integrate commercial and open-source LLMs into enterprise applications
• Develop prompt engineering workflows and support AI model evaluation and optimization
• Deploy and support AI applications on AWS cloud platforms
• Troubleshoot and optimize AI systems for latency, reliability, scalability, and cost efficiency
• Collaborate with cross-functional teams across onshore and offshore locations
• Write clean, maintainable, and testable code following software engineering best practices
• Participate in code reviews, unit testing, integration testing, and CI/CD processes

Gen AI Developer – Python, FAST API

• Collaborate with application teams to integrate solutions with products and platforms, aligning with technology strategy and business outcomes
• Architect and design reusable services leveraging and integrating frameworks for optimal performance and compatibility
• Perform hands-on coding while prototyping proof-of-concepts
• Own overall system quality and implement best practices
• Perform code reviews and code quality checks to promote maintainable and scalable code
• Serve as the technology point of contact for business partners and application teams
• Mentor and provide technical guidance to junior programmers and software engineers
• Troubleshoot issues and perform root cause analysis
• Design scalable AI workflows and integrate autonomous agents into real-world applications
• Translate cutting-edge AI capabilities into reliable business solutions

Gen AI Developer, Python – FAST API

• Own end-to-end program delivery across scope, timelines, quality, throughput, contributor performance, and cost.
• Design and manage workflows for coding datasets, agentic trajectories, RL environments, benchmarks, and rubric-based evaluations.
• Identify operational bottlenecks and improve workflows through better instructions, sequencing, incentives, review systems, and capacity planning.
• Define contributor requirements and partner with talent teams to source, assess, onboard, train, and ramp distributed software engineers.
• Build team-lead and reviewer structures for programs involving 100–1,000+ contributors.
• Own quality-control systems and analyze datasets to identify trends, systematic errors, and root causes.
• Act as a primary customer contact for AI labs, communicating progress, risks, quality trends, and recovery plans.
• Translate research objectives into practical task specifications and challenge requirements when they may not produce the intended evaluation signal.
• Use Python, SQL, or similar tools to automate quality sampling, defect analysis, throughput reporting, and operational reviews.
• Convert successful workflows into reusable playbooks, quality controls, evaluation assets, and contributor-management systems.
• Share operational learnings and mentor other program leads.

Technical Program Operations Lead – AI Engineering

• Design, develop, and implement AI/ML and Generative AI solutions for enterprise business applications
• Build and deploy applications leveraging Large Language Models (LLMs), Retrieval-Augmented Generation (RAG) architectures, vector databases, and agent-based frameworks
• Develop AI-powered solutions for document processing, information extraction, knowledge management, recommendation systems, virtual assistants, and conversational AI applications
• Integrate AI applications with APIs, databases, cloud platforms, and enterprise systems
• Collaborate with business stakeholders, domain experts, and engineering teams to translate business requirements into scalable AI solutions
• Support deployment, optimization, monitoring, and continuous improvement of AI applications in production environments
• Stay current with emerging AI technologies and industry best practices to drive innovation and adoption across the organization
• Mentor junior developers and contribute to technical leadership initiatives

Lead AI/ML Engineer

• Drive technical direction for agentic AI initiatives, influencing architecture patterns, autonomy boundaries, and system design
• Design, build, and operate production-grade agentic AI systems used across multiple products
• Own and evolve agent frameworks, orchestration layers, planning, tool use, memory strategies, RAG pipelines, LLM infrastructure, inference, model gateways, evaluation, observability, and safety tooling
• Lead technical design reviews and guide tradeoffs involving autonomy, safety, reliability, scalability, and cost
• Partner across teams to deliver complex, cross-cutting agentic AI initiatives from concept to production
• Evaluate emerging models, techniques, and agentic patterns and translate them into enterprise-ready improvements
• Mentor senior engineers and raise the technical bar for agentic AI development
• Architect and own coordination across multiple platforms, ensuring scalability, resiliency, and compliance with global standards
• Build proofs of concept to experiment with new technologies, databases, and application infrastructure
• Pursue innovative technologies and open-source products for low-latency distributed systems
• Drive a culture of innovation and experimentation
• Provide technical consulting support to global product teams and regional stakeholders for secure product rollouts
• Partner with risk, compliance, and cybersecurity teams to meet regulatory and security requirements
• Work with peers, Principal Engineers, and Principal Architects to incorporate new technology and delivery methods into scalable software solutions

AI Engineer jobs in India