• Design, develop, and deploy production-grade applications leveraging various LLMs, context optimization, etc. • Architect and implement sophisticated, multi-step and multi-agent workflows using frameworks like LangChain and LangGraph. • Build and optimize RAG pipelines, including implementing and managing embeddings, vector databases, and advanced rerankers to enhance response quality and relevance. • Use code generation applications (e.g. Replit, Cursor, Google AI Studio, Git Hub Copilot in Agent mode, etc.) to create full applications (including frontend and backend), generate tests, perform testing and integrate them in the core product without writing any code. • Lead efforts in LLM fine-tuning (e.g., LoRA, QLoRA) for specific domain knowledge and tasks, and implement strategies for and efficiency. • Develop and refine advanced prompt engineering techniques to maximize model performance, consistency, and safety. • Own end-to-end implementation from frontend to the backend. • Expose AI/LLM functionality written in Python using Java services, leverage multi-threading capabilities in Java to augment AI/LLM functionality developed in Python. • Utilize AI-powered development tools (e.g., GitHub Copilot, etc.) to efficiently generate, refactor, and optimize high-quality code. • Work closely with team leads managers, QA, product managers and team in the US (this will require the willingness to partially work US working hours)

• Build & Ship AI-Powered Products • Design, develop, and deploy LLM-powered applications and agent-based systems in production • Own the full product lifecycle from concept → production → iteration across backend and frontend • Build scalable, maintainable systems that solve real customer problems • Develop prompt strategies, context management (RAG, memory), and agent workflows • Integrate and optimize across leading LLM APIs (OpenAI, Anthropic, Gemini, open-source) • Continuously improve system quality, reliability, and performance • Use AI-assisted coding tools (e.g., Cursor, Copilot, Claude Code) to accelerate development • Validate, test, and safely integrate AI-generated code into production systems • Own testing strategy including unit, integration, and end-to-end testing • Define and implement evaluation frameworks for AI outputs (quality, consistency, failure modes) • Debug production issues and optimize for latency, cost, and scalability • Translate ambiguous requirements into working solutions • Partner with product, design, and customer-facing teams to deliver impactful features • Collaborate effectively with distributed and offshore engineering teams

Founded in 2021, Pulsora the “Enterprise Sustainability Platform”, is a well-funded Silicon Valley software startup. It is dedicated to empowering purpose-driven enterprises to manage and improve their environmental, social, and governance (ESG) and overall sustainability footprint with an integrated, comprehensive, flexible, and innovative technology platform built for compliance, tracking, and insight. We are well funded, have amazing customers across industries and geographies, established strategic partnerships with leading ERP and consulting firms, and are growing fast! About the job We are seeking a highly skilled and experienced engineer who can independently build and scale full-stack products while designing and deploying reliable LLM-powered systems and agent workflows in production. What you will do - Build & Ship AI-Powered Products - Design, develop, and deploy LLM-powered applications and agent-based systems in production - Own the full product lifecycle from concept → production → iteration across backend and frontend - Build scalable, maintainable systems that solve real customer problems - Design & Operate GenAI Systems - Develop prompt strategies, context management (RAG, memory), and agent workflows - Integrate and optimize across leading LLM APIs (OpenAI, Anthropic, Gemini, open-source) - Continuously improve system quality, reliability, and performance - Leverage AI-First Development Workflows - Use AI-assisted coding tools (e.g., Cursor, Copilot, Claude Code) to accelerate development - Validate, test, and safely integrate AI-generated code into production systems - Contribute to evolving best practices for AI-first engineering - Ensure Quality, Reliability & Performance - Own testing strategy including unit, integration, and end-to-end testing - Define and implement evaluation frameworks for AI outputs (quality, consistency, failure modes) - Debug production issues and optimize for latency, cost, and scalability - Take full ownership of system reliability and production stability - Collaborate & Execute in Fast-Moving Environments - Translate ambiguous requirements into working solutions - Partner with product, design, and customer-facing teams to deliver impactful features - Collaborate effectively with distributed and offshore engineering teams - Advance AI & Product Capabilities (Nice to Have Contributions) - Build advanced agent systems (planning, orchestration, parallel execution) - Apply frameworks like LangChain, LangGraph, or similar where appropriate - Explore fine-tuning, evaluation frameworks, and benchmarking techniques - Contribute to intuitive, user-friendly AI-driven experiences and human-in-the-loop workflows About you - Bachelor’s degree in Computer Science, Engineering, or related field preferred (or equivalent hands on experience) - 1-2 years of experience building AI-powered applications (AI agents or AI-assisted coding) and building and deploying LLM-powered applications or agents in production - Experience integrating major LLM APIs (e.g., OpenAI, Anthropic, Gemini, open-source) - Working knowledge of prompt design, context management (RAG, memory, tool use), and multi-step/agentic workflows - Ability to take products from concept to production and iteration across backend and frontend systems, including working across the full engineering lifecycle - Practical experience using tools like Claude Code, Cursor, OpenAI, Microsoft Copilot, including the ability to safely integrate AI-generated code into production (validation, CI/CD) - Experience debugging production issues, optimizing performance (latency, cost), and building maintainable systems - Ability to define evaluation strategies for AI outputs (quality, consistency, failure modes) and experience with AI-driven testing and reliability practices A little more about how you like to work - Strong collaboration across a small team, including great communication with both onshore and offshore departments and translating vague requirements into actionable systems. - Self-motivated and proactive—you create momentum without needing direction - A strong problem solver who can navigate ambiguity - A builder who cares about shipping real, working products - Comfortable with ownership, accountability, and high expectations - Thrives outside of traditional work structures - You own the quality of the product you build Why this role? - High ownership and autonomy - Opportunity to build products end-to-end using AI-first workflows - Work at the cutting edge of AI-driven software development - Work with multiple leading-edge technologies - Fast-moving, execution-focused culture - Work for the industry leader and innovative company - You get to work on a solution that helps the planet and helps us all Why work at Pulsora? We believe that progress happens by bringing together people from all walks of life who have the drive and the influence to improve our world now and for the next generations! - Ideally have industry and market knowledge of ESG and sustainability - The company will pay with salary, equity, and benefits - You’ll get to work on problems that are hard and important - You get to work on a solution that helps the planet and helps us all - You’ll be joining an extraordinary team at the beginning of an extraordinary journey - Hybrid-friendly work environment, in office 2-3 times per week (for those in New York, San Francisco Bay Area, and Munich) Pulsora Core Values - Compassionate candor - Transparency - Embrace diversity and cultivate belonging - Make a positive impact - Delight customers Join us and become a driver for positive change!

Industry/Sector Not Applicable Specialism Managed Services Management Level Senior Associate Job Description & Summary At PwC, our people in managed services focus on a variety of outsourced solutions and support clients across numerous functions. These individuals help organisations streamline their operations, reduce costs, and improve efficiency by managing key processes and functions on their behalf. They are skilled in project management, technology, and process optimization to deliver high-quality services to clients. Those in managed service management and strategy at PwC will focus on transitioning and running services, along with managing delivery teams, programmes, commercials, performance and delivery risk. Your work will involve the process of continuous improvement and optimising of the managed services process, tools and services. Focused on relationships, you are building meaningful client connections, and learning how to manage and inspire others. Navigating increasingly complex situations, you are growing your personal brand, deepening technical expertise and awareness of your strengths. You are expected to anticipate the needs of your teams and clients, and to deliver quality. Embracing increased ambiguity, you are comfortable when the path forward isn’t clear, you ask questions, and you use these moments as opportunities to grow. Examples of the skills, knowledge, and experiences you need to lead and deliver value at this level include but are not limited to: - Respond effectively to the diverse perspectives, needs, and feelings of others. - Use a broad range of tools, methodologies and techniques to generate new ideas and solve problems. - Use critical thinking to break down complex concepts. - Understand the broader objectives of your project or role and how your work fits into the overall strategy. - Develop a deeper understanding of the business context and how it is changing. - Use reflection to develop self awareness, enhance strengths and address development areas. - Interpret data to inform insights and recommendations. - Uphold and reinforce professional and technical standards (e.g. refer to specific PwC tax and audit guidance), the Firm's code of conduct, and independence requirements. GenAI Site Reliability Engineer Observability | Incident Response | Reliability Engineering | AWS and GenAI Operations Purpose: Operate, monitor, and continuously improve the reliability of in-scope AI platforms and services. Role GenAI Site Reliability Engineer Level AC - Staff - Experienced Tower AI Operations & Platform Support (AI Managed Services) Experience 4+ years in SRE, production support, cloud operations, or a similar run-state engineering role Work Location Bangalore / Hyderabad, India (Remote) Key Platforms AWS / Amazon Bedrock, OpenAI / ChatGPT Enterprise, observability and ITSM tooling Role profile Hands-on reliability engineer focused on monitoring, incident response, service health, and operational stability for AI workloads. Primary focus Observability, alerting, incident investigation, RCA support, automation, and post-change validation. Best fit An engineer who likes messy production problems, can separate signal from noise, and is comfortable owning issues through restoration and follow-up. Role Summary As a GenAI Site Reliability Engineer, you will operate and improve monitoring for in-scope AI services, investigate incidents, restore service, and implement reliability improvements. The role is oriented around real run-state support rather than net-new build work, so we need people who can work from alerts, logs, traces, tickets, dashboards, and imperfect documentation to drive structured troubleshooting and better outcomes over time. Key Responsibilities 1. Monitoring, alerting, and service health - Build and maintain dashboards and alerts for availability, latency, error rates, usage, and other service-health indicators. - Tune thresholds and alert routing to reduce noise and improve actionable detection, MTTA, and MTTR. - Monitor platform health across AWS and GenAI services and escalate emerging issues before they become user-impacting incidents. 2. Incident triage, restoration, and problem management - Investigate incidents using logs, metrics, traces, ticket history, and runbooks; execute restoration steps and coordinate escalation when deeper resolver groups are needed. - Contribute to RCA and post-incident corrective actions for major incidents and recurring issues. - Support severity assessment with the incident commander and provide clear technical updates during active events. 3. Reliability improvement and automation - Identify recurring failure modes and implement improvements such as alert tuning, diagnostics automation, repeatable checks, or resilience enhancements. - Automate routine support activities to reduce manual effort and improve consistency of triage and recovery. - Support performance and cost troubleshooting by isolating contributing factors and validating the impact of fixes. 4. Operational readiness and knowledge management - Maintain runbooks, known-error patterns, troubleshooting guides, and standard operating procedures. - Support change readiness and post-change validation so monitoring, documentation, and restoration steps stay current as the platform evolves. - Provide inputs to service reporting on trends, recurring issues, and improvement opportunities. Preferred Skills and Experience Skill area Preferred background SRE and production operations Hands-on experience supporting production services in a cloud environment, including monitoring, troubleshooting, incident response, and restoration. Observability Experience building dashboards and alerts and using logs, metrics, and traces to diagnose issues. CloudWatch, Datadog, Splunk, New Relic, Grafana, or OpenTelemetry experience is relevant. Cloud and GenAI platform operations Working knowledge of AWS operations and familiarity with Bedrock, OpenAI, or adjacent AI platform services used in enterprise production environments. Incident and problem management Experience working within ITIL-aligned processes for incident, problem, request, and change management, including strong ticket hygiene and runbook discipline. Automation and scripting Ability to automate diagnostics or repetitive support activities using Python, shell scripting, or similar tools. Critical thinking and collaboration Ability to solve ambiguous production issues, work across teams, ask the right questions, and engage stakeholders to move investigations and actions forward. Nice to Have • Experience supporting Bedrock or OpenAI-powered workloads in production. • Experience with service reliability metrics such as SLIs, SLOs, MTTA, MTTR, and error trends. • Exposure to cost and usage monitoring, quota or throttling investigation, and post-change validation. • AWS certifications or other cloud reliability certifications. Working Style & Core Behaviors - Thinks in a structured, evidence-based way and does not jump to conclusions. - Can stay effective when documentation is incomplete and the right path is not obvious up front. - Communicates clearly during live incidents and keeps others aligned on status, risks, and next steps. - Works well with engineers, platform owners, service desk teams, and vendors without creating friction. What Good Looks Like - Can trace a noisy alert to a meaningful root cause and either restore service or escalate with the right evidence. - Improves monitoring quality over time instead of simply reacting to tickets. - Turns recurring pain points into automation, better documentation, or better alert logic. - Builds confidence with stakeholders because updates are clear, grounded, and action-oriented. Team Context You will join PwC’s AI Operations & Platform Support team supporting a clients’ run-state AI environment. The operating model is centered on Level 2 and Level 3 support, monitoring, incident response, service requests, minor enhancements, and continuous improvement across AWS/Bedrock, OpenAI, and related platform components. This role will work in a managed-services model focused on incident management, service requests, monitoring, minor enhancements, knowledge management, and continuous improvement. Success depends not only on technical skill, but also on ownership, collaboration, and the ability to engage stakeholders to progress work. Travel Requirements 0% Job Posting End Date