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Secure Every Identity, from AI to Human Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence. This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk. As a Senior Site Reliability Engineer you will champion all things pertaining to reliability at Okta for Auth0. Working closely with the Product Engineers, Quality Engineers, Platform Engineers and Architecture teams, your primary focus will be on ensuring production systems remain operational at all times, while continually setting and achieving long-term performance, reliability and scalability goals in a platform with an exponential growth plan for the coming years. With Okta’s increased dedication to ensuring customer availability expectations are exceeded in every way, you will play a key role as we evolve our system architecture to meet the demands of enormous growth and support the hundreds of millions of users who rely on us to provide uninterrupted access to business-critical enterprise and consumer applications. Skills Exceptional communication skills, including technical writing in the English language Systematic problem-solving approach, coupled with a strong sense of ownership and drive Understanding of microservices, cloud infrastructure (AWS, Azure), databases (SQL, No-SQL, Key/Value), containers (docker, kubernetes), web technologies (web sockets, http) and networking (SSL, routing, VPN) Live and breathe SLIs, SLOs, error budgets and SLAs Strong belief in automating everything and reducing toil for yourself and teammates Loves to work as a team, but is able to work effectively in a remote environment where tasks may be self-driven Knowledge

We’re looking for an HR Associate to join our People Operations team at Bolna.ai . This is a hands-on HR Operations role for someone who enjoys working closely with employees, keeping processes smooth, and making sure the day-to-day employee experience runs seamlessly. What you’ll do Manage employee onboarding, documentation, and joining formalities . Prepare and manage HR letters, employee documentation, and records . Maintain accurate and up-to-date employee data across HR systems . Coordinate with HR and external vendors for employee-related processes and requirements. Support employee engagement activities, events, and team-building initiatives . Help drive smooth execution of day-to-day HR Operations and employee queries . Identify process gaps and help build simpler, more efficient HR processes as we scale. Who we’re looking for 6 months–1 year of experience in HR Operations / People Operations. Strong understanding of employee lifecycle processes and HR documentation . Excellent communication and interpersonal skills . Highly organised, detail-oriented, and comfortable managing multiple priorities. Proactive, dependable, and willing to take ownership and figure things out . Comfortable working in a fast-paced startup environment. Immediate joiners are preferred. Why this role? You’ll get hands-on exposure to HR Operations, employee experience, engagement, and people processes in a rapidly scaling startup. You’ll work closely with the People team and employees across the organisation, with the opportunity to take ownership, build processes, and grow with the company . High ownership. Fast learning. Real impact. Location: Bellandur, Bangalore Working Days: Monday–Friday

At Bolna, we’re building tools that change the way teams leverage Voice AI. We’re looking for a Founding Machine Learning Engineer to own the end-to-end lifecycle of building, evaluating, deploying, and improving models that power millions of production conversations. This is a high-impact, high ownership role where you won’t just work on Bolna’s ML stack—you’ll help build the foundation it scales on. Our team includes IIT alumni with experience at Bain, Atlassian, Uber, Zomato, and LinkedIn, and is backed by leading investors. Responsibilities: Build the data engine - Design pipelines to source and clean conversational voice data across Indian languages, accents, and telephony conditions. Fine-tune models that ship - Fine tune and train models to improve accuracy, speed, and reliability across different use-cases. Define what "good" means - Build evaluation datasets and benchmarks for transcription accuracy, voice naturalness, interruption handling, latency, and end-to-end conversation quality. Set up human-in-the-loop pipelines to capture subjective quality at scale. Ship to production - Work with the engineering team to deploy models into a latency-sensitive, high-volume system. Monitor performance in the wild, debug regressions, and iterate fast. Required Skills: 3+ years of hands-on ML experience with deep practical real-world experience in training models. Strong Python and PyTorch fundamentals with exposure in distributed training, and modern fine-tuning techniques (LoRA, QLoRA, DPO, RLHF, etc.). Training data as a first-class problem. Experience designing data pipelines from collection, cleaning, labeling, deduplication, augmentation and treating data quality as a core engineering discipline. Rigorous about evaluation. You know that "looks good in a demo" is not a benchmark. You build the evals before you trust the model. Speech model experience is a plus with real-time / streaming inference experience where you would have contributed to latency optimization

About Ema Ema is building the world’s leading Agentic AI platform to transform enterprise productivity. We enable organizations to delegate repetitive tasks to Ema, the Universal AI Employee, delivering 10x gains in workforce efficiency, across functions. Founded by former executives from Google, Coinbase, Flipkart, and Okta, our team includes engineers from premier tech companies and graduates of Stanford, MIT, UC Berkeley, CMU, and IITs. We are backed by industry leading investors including Accel, Naspers/Prosus, Section32, and angels like Sheryl Sandberg and Dustin Moskovitz. Headquartered in Silicon Valley and with offices in London, Bangalore and Vancouver, Ema is at the frontier of what Agentic AI can do in production — we ship real systems that run real business processes at scale. The Role The Customer Engagement Manager owns a portfolio of strategic enterprise accounts end-to-end: every engagement, every outcome, every relationship, every expansion opportunity. Think of this as the McKinsey Associate Partner model applied to enterprise AI delivery. You are the single point of accountability for your accounts. The customer calls you — not your manager — when they have a problem. You staff delivery teams, oversee solution quality, run executive readouts, measure ROI, drive adoption, rebuild trust when things break, and grow the book through proven production value. This is not a project management role. This is an account ownership role that combines delivery orchestration, outcome ownership, customer leadership, and commercial growth. What You’ll Own 1. Account Ownership Own your accounts end-to-end: every engagement, every outcome, every relationship. Everything good or bad stops with you. Be the single point of contact the customer calls for any problem — delivery, quality, adoption, escalation, or expansion. Maintain a holistic view of each account: engagement status, risk exposure, opportunity pipeline, and the customer’s strategic priorities for the qua