Ai Reimagination Engineer in India

We’re looking for a Talent Acquisition professional to join the People team at Bolna.ai . This is a hands-on role for someone who understands the nuances of hiring , thrives in a fast-paced environment, and knows how to build pipelines, convert strong candidates, and help teams hire exceptional talent at speed. What you’ll do Own end-to-end hiring across multiple functions — from understanding the requirement and sourcing to interviews, offers, and closures. Partner closely with hiring managers and leadership to understand hiring needs, define candidate profiles, and drive focused hiring strategies. Build and maintain strong talent pipelines through LinkedIn, referrals, communities, databases, and creative sourcing channels . Understand the nuances of hiring — what to look for, where to find the right talent, how to engage candidates, and how to convert them . Drive fast-paced hiring without compromising on candidate quality or experience. Build strong candidate relationships and effectively manage the funnel from first conversation to closure . Own and strengthen employee referral programs , finding creative ways to increase participation and conversions. Track pipeline health and hiring metrics, identify bottlenecks, and continuously improve the hiring process. Contribute to employer branding, talent mapping, and other hiring initiatives as Bolna scales. Who we’re looking for 3–6 years of experience in Talent Acquisition / Recruitment, preferably in a startup or high-growth environment. Strong understanding of fast-paced hiring and high-volume / multi-role recruitment . Excellent sourcing, screening, candidate engagement, and offer conversion skills. Strong understanding of the nuances of hiring and building quality talent pipelines . Experience managing or building employee referral programs . Strong communication, stakeholder management, and negotiation skills. High ownership, urgency, and attention to detail. Someone who enjoys figuring things out, moving fast,

We’re looking for a technical force multiplier to work directly with the founders at Bolna.ai . This is not a traditional Chief of Staff, PM, or engineering role. It sits at the intersection of strategy + product + engineering. Your job is simple: take messy, important problems, figure out what matters, and make things happen. What you’ll do Find and build ways to leverage AI internally to dramatically improve engineering velocity and company operations. Dive into product, business, growth, and engineering data to uncover insights and turn them into clear, actionable recommendations. Work across Engineering, Product, and Growth to supercharge teams, remove bottlenecks, and unlock leverage through technology. Pick up ambiguous, high-leverage problems and drive them end-to-end. One day could mean discovering and iterating on a new tool in the morning, building a prototype that afternoon, and shipping it by the end of the day. Who we’re looking for You have high agency and a founder’s mindset . You’re technically strong enough to build prototypes, deeply curious about how things work, and fast at learning unfamiliar domains. You have strong product and business intuition, can reason from messy data, and communicate clearly in writing. You’d rather skip a one-hour meeting to spend that hour chasing a curiosity that could create 10x the impact . You know that disproportionate outcomes often come from asking the question nobody assigned you to ask. You don’t wait for perfectly scoped tasks. Depending on the problem, you’re comfortable researching, coding, analyzing data, talking to customers, testing a product, or coordinating a team. Most importantly, you have good judgment about what is worth pursuing . If you’re an ex-technical founder or founding engineer , this role will likely feel familiar: high ambiguity, high ownership, and a bias toward figuring things out yourself. We operate with a simple belief: AI, when applied skillfully to the right problems, can create di

About Bolna Bolna is a YC-backed voice AI orchestration platform built for the Indian market—powering multilingual, vernacular voice agents across Hindi, Hinglish, Tamil, and 10+ languages at sub-500ms latency across collections, recruitment, sales, and e-commerce use cases. We are an orchestration layer, not a model company: our moat is outcome-labelled vernacular data, rigorous evaluation infrastructure, and a growing taxonomy of how Indian enterprise voice AI fails in production. Why This Role Exists Product decisions at Bolna increasingly hinge on rigorous, code-mixed-aware data analysis—and not just one kind. On one side, there is model and evaluation rigor: LLM benchmarking for post-call intelligence, ASR/WER evaluation, inter-rater reliability on human-labelled calls, and routing and latency economics. On the other, there is product and growth insight: understanding where self-serve users drop off in their journey, what patterns emerge across lakhs of monthly calls, and which use cases and configurations are actually working. Both currently sit with the Head of Product alongside strategy and roadmap ownership. We need a dedicated analyst to own the execution and recurring cadence across both-freeing product leadership to act on findings rather than produce them. What You’ll Do Model and Evaluation Analysis LLM and model benchmarking: Run structured comparisons across model providers such as Sarvam, DeepSeek, Gemini, and Claude variants for tasks including post-call extraction and LLM-as-judge scoring. Evaluate cost, accuracy, fill rate, and TTR, with particular attention to Hinglish and code-mixed content. Evaluation infrastructure: Build and maintain LLM-as-judge pipelines using tools such as DeepEval, design and track evaluation metrics, and run inter-rater reliability analysis such as Krippendorff’s alpha across human call reviewers. Golden dataset creation: Support the construction of golden datasets for ASR and transcript labelling, including flagging co

About Forma.ai: Forma.ai is a Series B startup that's revolutionizing how sales compensation is designed, managed and optimized. We handle billions in annual managed commissions for market leaders like Edmentum, Stryker, and Autodesk. Our growth has been fuelled by our passion for fundamentally changing and shaping how companies use sales intelligence to drive business strategy. We’re welcoming equally driven individuals who are excited about creating something big! About the team: The Customer Operations team is at the heart of Forma.ai's mission. This team has a direct impact on the growth of Forma.ai. They are results-driven and solutions-minded. The Customer Operations team works closely with our customers, helping them to understand and take advantage of all the features Forma.ai offers and ensuring that they get the most value from the platform. What you'll be doing: Reporting to the Senior Manager of Customer Operations, the Incentive Compensation Associate (known internally as Customer Operations Associate) will be contributing in the following areas: Own the ongoing operations for a portfolio of customers (i.e., rule building, process execution, reporting and dashboarding, and product support) Create automated reporting (financial, sales performance, incentive compensation) for customers to support process automation and improve business visibility Support design projects including analysis, financial modelling, project planning, customer workshops, and presentation/recommendation of findings Identify potential opportunities for process improvement in client processes (e.g., process execution, data validation, dashboard updates). Explore new techniques, working models to improve design and improve processes. Implement new Forma.ai platform features within your customer portfolio to support continuous improvement and automation Build strong working relationships with key customer stakeholders, ens

About Forma.ai: Forma.ai is a Series B startup that's revolutionizing how sales compensation is designed, managed and optimized. We handle billions in annual managed commissions for market leaders like Edmentum, Stryker, and Autodesk. Our growth has been fuelled by our passion for fundamentally changing and shaping how companies use sales intelligence to drive business strategy. We’re welcoming equally driven individuals who are excited about creating something big! About the team: The Customer Operations team is at the heart of Forma.ai's mission in optimizing incentive compensation plans for all companies . They wo rk directly with our customers in helping them understand and take advantage of all the sales compensation features Forma.ai offers . F rom streamlining administration and management of sales commission to designing your sales compensation plan , o ur Customer Operations team ensur es customers get the most value from our platform in optimizing every dollar spent on sales compensation. What you'll be doing: Reporting to the Senior Manager of Customer Operations, the Incentive Analytics Manager will contribute in the following areas: Develop a strong understanding of the Forma.ai product and platform to establish yourself as a product expert Lead the ongoing operations for a portfolio of customers (i.e., commissions rule building, process execution, reporting and dashboarding, and overall product support) Implement new Forma.ai platform features within your customer portfolio to support continuous improvement and automation Identify potential opportunities for process improvement in client processes (e.g., process execution, data validation, dashboard updates). Explore new techniques, working models to improve design and improve processes Lead design projects, including analysis, financial modelling, project planning, customer workshops, and presentation/recommendation of findings

About Forma.ai: Forma.ai is a Series B startup that's revolutionizing how sales compensation is designed, managed and optimized. We handle billions in annual managed commissions for market leaders like Edmentum, Stryker, and Autodesk. Our growth has been fuelled by our passion for fundamentally changing and shaping how companies use sales intelligence to drive business strategy. We’re welcoming equally driven individuals who are excited about creating something big! About the team: The Customer Operations team is at the heart of Forma.ai's mission. This team has a direct impact on the growth of Forma.ai. They are results-driven and solutions-minded. The Customer Operations team works closely with our customers, helping them to understand and take advantage of all the features Forma.ai offers and ensuring that they get the most value from the platform. What you'll be doing: Reporting & Dashboarding Design, maintain, and enhance dashboards in BI tools (e.g., Looker Studio, Salesforce/HubSpot reports) to monitor marketing campaign performance, sales pipeline health, lead flow, and conversion metrics Automate recurring reports and implement self-serve analytics capabilities for GTM teams Data Analysis & Insights Analyze funnel performance from top-of-funnel marketing campaigns to bottom-of-funnel sales outcomes Provide regular insights into key KPI s like campaign ROI, customer acquisition cost (CAC), and attribution across channels Support A/B testing initiatives, sales activity analysis, and segmentation strategies Scripting & Automation Write Python and SQL scripts to extract, clean, and structure data from external sources (e.g., job boards, press releases, M&A feeds, web scraping APIs ) Build automated enrichment pipelines to augment CRM and marketing data with third-party insights (e.g., firmographics, hiring activity, technology stack, fun

About Forma.ai: Forma.ai is a Series B startup that's revolutionizing how sales compensation is designed, managed and optimized. We handle billions in annual managed commissions for market leaders like Edmentum, Stryker, and Autodesk. Our growth has been fuelled by our passion for fundamentally changing and shaping how companies use sales intelligence to drive business strategy. We’re welcoming equally driven individuals who are excited about creating something big! About the Team: The Customer Operations team works closely with new and existing customers by implementing product features, managing the operational parts of the platform, and optimizing our client’s sales performance management processes. We are always ready to support and help our customers to identify ways they can unleash the revenue-driving potential of their sales compensation program. If you’re passionate about data analytics and want to contribute to sales operations, we’d love to hear from you! What you’ll be doing: • Work with new and existing customers to implement the company's new platform features as well as manage and optimize client processes • Learn the architecture and design of the company's platform to the extent of being able to independently complete updates, enhancements, and change requests • Lead onboarding & activities, including requirements gathering for incentive compensation plan rules, data analysis, and quality control • Assist the ongoing operations for a portfolio of existing customers and implement new features (i.e. rule building, process execution, reporting and dashboarding, and product support) • Scope, build and test automated workflows, processes and reporting capabilities to support automation of incentive compensation processes and improve business visibility • Support design projects including analysis, financial modelling, project planning, customer workshops

About Us Oliv.AI is a SalesTech global startup headquartered in San Francisco, debuting the world's first team of AI Agents for sales. With our recent $5.2M Seed funding, we solve one of the biggest problems for revenue teams: unreliable deal data. Oliv captures Deal Intelligence from every meeting, call, and email—without any rep involvement. The result is a clear, detailed view of every deal, presented in scorecards built on trusted sales methodologies like MEDDICC, BANT, and SPICED. Our AI agents are built for sales teams—sales managers, AEs, and RevOps—handling the work that takes them away from selling. With Oliv AI, sales teams can bring back focus on deals, strategy and conversation. About the Role We’re looking for an exceptional engineer to join the core team at Oliv AI. This is a high-ownership role for someone who can take an ambiguous product or engineering problem, figure out what actually needs to be solved, and drive it end-to-end from architecture and prototyping to production and iteration. You’ll primarily work on backend systems, but we don’t want engineers constrained by boundaries. If the problem requires frontend, infrastructure, data, AI/LLM integrations, or internal tooling, you should be comfortable figuring it out. We’re looking for someone with strong engineering judgment, someone who can spot what is not working, simplify complexity, think from the customer’s perspective, and improve the systems and practices around them. What You’ll Do Own complex, ambiguous engineering problems from first principles through production Design simple, scalable, reliable systems and make strong architectural trade-offs Think beyond the ticket and understand the customer problem behind what you’re building Identify technical or product issues proactively, not only when they are assigned Work across backend, frontend, infrastructure, data, and AI when needed Prototype quickly, test different approaches, and make decisions based on evidence Use mode

About Us Oliv.AI is a SalesTech global startup headquartered in San Francisco, debuting the world's first team of AI Agents for sales. With our recent $5.2M Seed funding, we solve one of the biggest problems for revenue teams: unreliable deal data. Oliv captures Deal Intelligence from every meeting, call, and email—without any rep involvement. The result is a clear, detailed view of every deal, presented in scorecards built on trusted sales methodologies like MEDDICC, BANT, and SPICED. Our AI agents are built for sales teams—sales managers, AEs, and RevOps—handling the work that takes them away from selling. With Oliv AI, sales teams can bring back focus on deals, strategy and conversation. The role This is not a traditional marketing role, and it is not a pure engineering role either. You will decide which accounts matter, build the systems that research them, write the content that reaches them, build the partnerships that amplify it, and turn all of that into qualified pipeline. Two things have to be true about you at once. You are technically sharp enough to build your own workflows, wire up your own APIs, and ship a working system without waiting on engineering or anyone else. Nothing you own should be blocked on a single person, including us. And you are obsessed with distribution — content, syndication, social, and partnerships — because pipeline goes to whoever the buyer already trusts. That means newsletters, communities, podcasts, comparison pages, partner audiences, and the people who influence them. What you will own GTM strategy and experimentation Develop and continuously refine Oliv's ICP, market segments, buyer personas, and account-selection criteria. Translate company goals into specific growth hypotheses and campaign plans. Identify new audiences, buying signals, use cases, and distribution opportunities. Build a structured experimentation roadmap across content, social, syndication, partnerships, outbound, and ABM. Define success metric

About the Role Together AI runs one of the largest GPU fleets in the world. The Infra Agent Systems team builds the software systems that power and automate that infrastructure. We develop production AI agents that diagnose hardware failures, investigate incidents, correlate signals across the fleet, and automate operational workflows. Alongside these agents, we build the platform they run on, including knowledge graphs, retrieval systems, orchestration frameworks, and developer tooling. You’ll work across two areas: Infrastructure Agent Systems — Build production AI agents that help operate our GPU fleet by diagnosing failures, investigating incidents, gathering evidence from live systems, and assisting with remediation. These agents are used every day by our infrastructure and datacenter teams through APIs, CLI, dashboards, and Slack. Core Agent Platform — Build the platform that powers these agents, including knowledge graphs, search and retrieval, orchestration, evaluation, and the tooling that enables agents to reason, act, and continuously improve. We’re working on something that hasn’t really been done before: building knowledge graphs and self-improving AI agents that understand, operate, and continuously improve large-scale AI infrastructure. This is an opportunity to work at the intersection of AI agents, distributed systems, infrastructure, and automation , solving challenging engineering problems with real production impact. There’s an enormous amount to build, learn, and shape as we define the future of autonomous infrastructure. responsible for delivering the software but also for operating and supporting it in production. Why this Role You’ll work on two hard problems at the same time: making AI agents trustworthy enough to operate production infrastructure, and building the knowledge, retrieval, and distributed systems that make those agents effective. You’ll have the opportunity to build foundational systems from the ground up, work on infrastructur

About the Role REMOTE IN INDIA We're looking for a software engineer to build the Kubernetes-native control plane that provisions and runs our GPU inference fleet. You'll design a manifest-driven API where the inference team declares what they need, whether that's a cluster, a model deployment, or a capacity change, and our controllers handle the reconciliation, provider/runtime selection, and lifecycle management underneath, so the inference team never has to know or care which specific serving stack, scheduler, or hardware pool is doing the work. You'll also build the systems that keep the fleet efficient, not just running, including defragmentation and rebalancing logic that consolidates scattered workloads back into contiguous capacity, and scheduling/bin-packing improvements that push GPU utilization up without hurting latency. The core value we're after is decoupling the people building on top of the platform from the operational and runtime complexity underneath, while squeezing more usable capacity out of the same hardware. You'll build the controllers, reconciliation loops, and self-service surface (API/CLI, not tickets) that make that decoupling real, plus the event-driven health, remediation, and utilization systems that keep it running and efficient without a human in the loop. Strong candidates have hands-on experience with Kubernetes controller/CRD patterns, have built or operated a platform API that abstracts multiple backends behind one interface, understand GPU scheduling and capacity efficiency (fragmentation, bin-packing, right-sizing), and think about GPU infrastructure as software to be engineered. A product mindset - you've built internal platforms or APIs consumed by other engineering teams and care about the developer experience of what you ship. You build it, you own it. You are not only responsible for delivering the software but also for operating and supporting it in production. Responsibilities Build the provisioning state machine

Scale is looking for a Support Systems & Routing Specialist to own and optimize the core infrastructure powering our contributor support operations. In this role, you will be responsible for configuring and maintaining systems like Zendesk, designing routing logic, and building scalable frameworks that ensure tickets are assigned accurately and efficiently. As our operations continue to grow, this role will play a critical part in ensuring our support systems scale seamlessly with increasing volume and complexity. You will partner closely with Support Ops, Product, Engineering, and cross-functional stakeholders to translate operational needs into robust system configurations. You will be part of a highly detail-oriented and systems-driven team, where your work directly impacts operational efficiency and contributor experience. This role is ideal for someone who thrives in building and improving systems that others rely on daily, and who enjoys solving complex operational challenges at scale. You will: Own end-to-end Zendesk configuration, including ticket forms, fields, macros, triggers, automations, SLAs, and views Design and maintain routing logic to ensure accurate ticket distribution across skills, queues, and teams Build and manage the support agent skills framework (skills, tiers, certifications, queue structures) Monitor and optimize queue health, load balancing, and ticket assignment accuracy Configure and maintain integrations across support tools and reporting systems Troubleshoot system issues and partner with Engineering or vendors when needed Collaborate with Support Ops, T&S, TPMs, and Product to implement and improve workflows Document system configurations, workflows, and best practices clearly Provide training and guidance to stakeholders on system usage and routing logic Ideally you’d have: Experience administering Zendesk or similar support CRM systems Experience designing routing logic or managing skills-based systems in high-volume envir

EnCharge AI is a leader in advanced AI hardware and software systems for edge-to-cloud computing. EnCharge’s robust and scalable next-generation in-memory computing technology provides orders-of-magnitude higher compute efficiency and density compared to today’s best-in-class solutions. The high-performance architecture is coupled with seamless software integration and will enable the immense potential of AI to be accessible in power, energy, and space constrained applications. EnCharge AI launched in 2022 and is led by veteran technologists with backgrounds in semiconductor design and AI systems. Senior Emulation Engineer Location: India - Remote Job Description: At EnCharge AI, we are building the next generation of AI compute silicon — purpose-built for high-performance, low-power, and scalable AI inference. As an Emulation Engineer, you will play a critical role in validating complex AI accelerator architectures on emulation platforms before tape-out. This position is ideal for someone passionate about bridging the gap between hardware and software in fast-paced, deep tech environments. Responsibilities: • Set up and maintain Siemens Veloce emulation and prototyping platforms • Adapt SoC designs for Emulation and Prototyping • Develop and debug emulation testbenches and system-level environments • Support pre-silicon validation, power/performance analysis, and early software bring-up. Participate in silicon bring-up and validation. • Collaborate with design and verification teams to isolate design issues and accelerate debug. • Optimize performance of the emulation workloads and reduce turnaround time. • Work with firmware/software teams to enable use of emulators for OS and driver testing. Required Background: • BS/MS/Ph.D. in EE, CS, or related field with 7+ years of SoC design experience. • Experience with emulation platforms (Veloce, Palladium, or ZeBu) and FPGA-based prototyping systems (proFPGA, HAPS, or Protium) • Experience with emula

About Bolna Bolna is Voice AI infrastructure built for India - and now for the world. We help businesses deploy intelligent voice agents that can call, converse, and convert in any language, at scale. From collections to customer support to sales, our agents handle millions of conversations so humans don’t have to. We’re a YC F25 company, backed by General Catalyst, with 1,050+ paying customers and growing fast. Our team of ~25 is based in Bengaluru. The Role Every voice AI agent Bolna deploys makes real-time judgment calls - when to speak, when to go silent, when a customer is done talking, when to hand off. We’re building automated systems to grade these calls at scale, using LLMs as judges of call quality. But before you trust a model’s judgment, you verify it against a human’s. That’s this role. You’ll listen to real calls, annotate what actually happened, and check whether our automated systems - LLM-as-judge evals and quantitative signal detection - got it right. It’s precise, high-attention work, and it sits right at the center of how we know our voice agents are actually working. This is an internship role for someone early in their career who wants hands-on exposure to how a voice AI company builds trust in its own AI. What You’ll Do Annotation Listen to and annotate real customer calls - transcription review, issue tagging, labeling - using tools like Label Studio Follow (and help sharpen) annotation guidelines for a multilingual environment (Hindi, English, Hinglish, ) Verifying LLM-as-Judge Evaluations For calls flagged by our automated eval pipeline, verify whether the model’s call was actually correct - for example, confirming whether a detected barge-in (agent/customer talking over each other) genuinely happened by listening to the audio Mark agreements and disagreements clearly, with reasoning, so we can measure and improve model accuracy over time All tools needed for this will be provided Verifying Quantitative Measures Check system-flagged quantit

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