Who gets hired and onto which teams
Coulomb AI employs ten people split between a San Francisco headquarters and a Bengaluru development center where every open role sits. Founders Khushboo Shrivastava and Santanu Mondal, both IIT Bombay alumni who cut their teeth on first-generation EVs at General Motors, have kept the hiring plan narrow: eight active salaried roles across four functional clusters, each tied to a distinct slice of a battery-analytics platform now operating in five countries.
The AI and data cluster carries the highest bar. The AI Engineer role demands six-plus years shipping production ML systems, expert-level Python and PyTorch or TensorFlow, fluency with MLOps tooling (MLflow, Kubeflow), distributed frameworks (Ray, Dask, Spark), and hands-on experience fine-tuning open-source foundation models (Llama, Mistral, DeepSeek) plus RAG pipelines, vector databases, and model serving infrastructure (vLLM, TGI, Ollama). The Senior Data Scientist slot requires three-plus years in time-series analysis, optimization, or computer vision, with the same expectation that models ship and hold up at scale. Both roles explicitly call for domain adjacency: battery electrochemistry, physics-informed ML, control systems, signal processing, or energy markets experience.
Platform and backend engineering sits in a second cluster. The Senior Backend Engineer demands six-plus years building distributed systems on cloud primitives (AWS, GCP, Azure). The Senior Full Stack Developer (six-plus years) and the Data Engineer (three-plus years) round out the data-plane team that ingests, stores, and serves the telemetry the AI models consume. A Frontend Web Developer role at two-plus years handles customer-facing dashboards; the Senior Frontend Developer - Analytics Platform (six-plus years) owns the heavier analytics surfaces.
The third cluster is a single, highly specialized seat: the Battery Modelling Engineer. Three-plus years developing lithium-ion, solid-state, or next-gen cell models, a master's in chemical engineering, materials science, or electrochemistry, fluency with COMSOL, MATLAB, and Python, and a publication record in peer-reviewed venues. This is not a generalist role — it anchors the domain the AI and platform teams build around.
The fourth cluster is product design: one UX Designer at one-plus years, tasked with making the analytics legible to fleet operators and energy traders.
No product management, no devops, no sales engineering, no QA — those functions either don't exist yet or are absorbed by the founders and the engineers themselves. The "ENGINEERING ENTERPRISE AI BATTERY MODELING INTERNSHIP" bucket on the company's own careers page confirms the same taxonomy: every hire maps to one of these four clusters. If your background doesn't slot cleanly into AI/ML production, backend/platform systems, frontend analytics, or electrochemical modeling, there is no adjacent role to grow into. The bar is high because the surface area is small.
What it pays
Coulomb AI lists compensation in U.S. dollars for every role on its Bengaluru-based team — a signal the company benchmarks against global AI talent markets rather than local IT-services pay scales. The figures come from live postings on Zero G Talent's board, which ingests salary bands directly from the company at publication. As of the latest intake, the board shows eight salaried openings with a combined band of roughly $23K–$70K (median $40K), according to Zero G Talent's board, across six distinct functions.
| Role | Location | Annual salary band (USD) |
|---|---|---|
| Senior Full Stack Developer | Bangalore | 50K–70K |
| AI Engineer | Bangalore | 40K–60K |
| Senior Data Scientist | Bengaluru, KA, IN | 25K–40K |
| Senior Backend Engineer | Bangalore | 30K–40K |
| Senior Frontend Developer - Analytics Platform | Bangalore | 30K–40K |
| Senior Frontend Developer | Bangalore | 20K–30K |
| Battery Modelling Engineer | Bangalore | 10K–14K |
| UX Designer | Bengaluru, KA, IN | 8K–12K |
The top of the band sits with the Senior Full Stack Developer role at $50K–70K, Zero G Talent's data shows, a range that overlaps senior IC compensation at well-funded Bay Area startups, yet the role is based in Bengaluru. The AI Engineer slot follows at $40K–60K, Zero G Talent's board found, reflecting the premium the founders place on model-deployment talent for their battery-observability platform. Data and backend engineering cluster in the $25K–40K band, according to Zero G Talent's board, while the two frontend listings split: the analytics-platform variant carries $30K–40K, the broader "Senior Frontend Developer" title $20K–30K; a gap that likely maps to the former requiring dashboarding and time-series visualization chops the latter does not.
At the lower end, the Battery Modelling Engineer role lists $10K–14K and the UX Designer $8K–12K. Those figures sit below market for similarly titled roles at Indian product companies, where mid-level designers often command $18K–$30K, suggesting Coulomb either treats these as junior/contributor tracks or expects the domain-specific battery modeling to be learned on the job. The company's own description, "building the critical intelligence layer for the global EV ecosystem right out of Bengaluru and San Francisco," implies a product org that prizes depth in electrochemistry-informed ML over generalist frontend or design polish.
All eight roles are salaried; the board shows no equity or variable components in the posted bands. Candidates should treat the USD figures as the total cash offer unless a separate equity grant is discussed in later stages. For benchmarking: a Bengaluru-based engineer with 4–6 years of full-stack or ML deployment experience typically sees $35K–$55K at Series A–B Indian SaaS startups, so Coulomb's top bands are competitive, while the bottom bands trail. The median $40K aligns with the company's Y Combinator-backed, pre-Series A stage and its stated headcount of roughly ten people, a small, high-trust team where each hire carries disproportionate product surface area.
How the hiring process works and what gets candidates through it
Coulomb AI's public hiring footprint is thin; the company careers page does not detail its funnel, and the company hasn't published a process manifesto. The Y Combinator job postings describe a process that starts with one or two video calls, then moves to onsite technical interviews and a culture-fit round. For the AI Engineer role: a first video call, a coding assessment focused on writing efficient and readable code, an algorithmic efficiency analysis, a technical interview with domain experts, and a culture-fit conversation. For the Battery Modelling Engineer: a first video call, two to three technical interview rounds, and a culture-fit round.
What disqualifies a candidate? Vague ownership stories, no evidence of shipping under constraint, and a mismatch with the narrow role scopes Coulomb AI actually posts. The board shows no junior roles, no generalist "software engineer" titles, and no remote listings. A candidate applying to the AI Engineer role with only LLM fine-tuning experience but no backend or data-pipeline work would face a steep gap. The company's posted bands ($8K–70K across roles, median $40K) reflect Bangalore-market senior pricing in USD terms, not Bay Area parity. Candidates who negotiate against a US benchmark without a competing offer stall the process.
The timeline from final conversation to offer can be fast. One Y Combinator-backed peer company states: "We aim to make a clear decision and, when there is a strong fit, extend an offer within a week of the final conversation." Coulomb AI's size — eight salaried roles on the board, two founders — means the decision loop is short, but the bar is high. The application that moves is the one that maps cleanly to a posted role, demonstrates production-grade engineering fluency, and shows a track record of shipping in the exact domain the role targets.
Where the work happens
Every role currently listed on Coulomb AI's board sits in Bengaluru, Karnataka; no remote, hybrid, or multi-city options appear in the board data. That concentration is intentional. Bengaluru remains India's densest cluster of EV OEMs, battery pack integrators, and the tier-one suppliers Coulomb's predictive analytics platform targets. The company's co-founders, Khushboo Shrivastava and Santanu Mondal, built the business there after Shrivastava's early career in automotive engineering (she specialized in a batch of sixty where only three women chose that track) and the Y Combinator acceptance in 2021 that made them the only woman co-founded tech company in that cohort. Proximity to customers in the automotive OEM, battery manufacturer, battery-as-a-service, and fleet segments shortens the feedback loop between battery telemetry coming off vehicles and the model updates Coulomb ships.
A UN Women profile from April 2023 notes the team at that time consisted of the two founders and "their team of AI experts and technical engineers, at least for now." The board's eight open roles, all senior, suggest the headcount is expanding from that core. Salary bands on the postings range from USD 8K–12K for the UX Designer to USD 50K–70K for the Senior Full Stack Developer, with a board-wide median around USD 40K. Those figures align with Bengaluru's senior-engineer market but sit below what the same roles command in Mumbai or Delhi NCR, reflecting a deliberate choice to hire locally at scale rather than compete for the handful of candidates willing to relocate.
The research does not show a second office, a satellite in Pune's automotive belt, or a formal remote policy. The job descriptions don't mention travel requirements. Candidates should assume an in-office default in Bengaluru unless a hiring manager states otherwise; early-stage climate-tech teams in this space tend to treat physical co-location as a speed advantage when iterating on hardware-adjacent software.
For an applicant, the takeaway is straightforward: if you are not already based in or willing to move to Bengaluru, Coulomb AI is not currently structured to accommodate you. The company's hiring signal — eight senior roles posted simultaneously in one city — reads like a team doubling down on its home base rather than distributing.
Who thrives here
Coulomb AI selects for people who treat the energy transition as an engineering problem, not a slogan. The company's own writing, CEO Khushboo Shrivastava's 2024 Medium post and the product pages at coulomb.ai, returns repeatedly to the mission: ensuring every battery in the field is safe, reliable, and sustainable, with a vision to reach net-zero emissions. A candidate who needs quarterly wins or visible feature velocity will frustrate fast. The work is battery modeling, electrochemical simulation, and the AI layer that turns noisy field data into predictive maintenance and second-life decisions, problems where the feedback loop is measured in months, not sprints.
The hiring record on Zero G Talent's board makes the profile concrete. Every open role sits in Bengaluru and carries a salary band between USD 8K and 70K (median ~USD 40K). That spread tells you two things: the team is small enough that titles map to scope, not hierarchy, and the compensation reflects an early-stage, cash-heavy calculus. People who optimize for cash compensation or brand-name prestige self-select out before the first screen.
Founders Santanu Mondal and Khushboo Shrivastava came out of Y Combinator S21 with a thesis that the battery value chain (chemistry, manufacturing, field operation, recycling) has been data-starved. Their product claims bear that out: Coulomb's platform provides real-time analysis of battery performance, increasing time efficiency and reducing total cost of ownership, with complete data transfer services from manual bookkeeping to software, improving battery health and decreasing failures and downtime. Shipping that stack requires engineers who can move across the stack (firmware to cloud to ML model) without waiting for a handoff document. The Battery Modelling Engineer role explicitly demands electrochemical domain knowledge; the AI Engineer role expects production-grade ML ops. A pure software generalist who treats the battery as a black box will not pass the technical bar.
The climate framing is explicit and operational, not performative. "With the constant rise in extreme temperatures, fires, floods, and other disasters happening more often, it's easy to feel overwhelmed," that line from the founding post reads like a requirements doc. The team builds for the edge cases that kill lithium-ion packs in the field. Candidates who have shipped hardware-adjacent software in regulated environments (automotive, aerospace, medical devices, grid infrastructure) recognize the constraint set. Those who haven't will spend their first months learning why "move fast and break things" gets you fired when the thing is a stationary storage asset.
The signal is the roadmap: solving battery lifecycle problems for customers across five countries. If your motivation compounds on that problem, if you read the mission and ask what the test protocol was, you will fit. If you read it and wait for the marketing deck, you won't. The interview process tests exactly that orientation: depth in one hard domain, breadth across the stack, and a default to automation over manual process. The company does not hide the difficulty. "However, accomplishing this task is no simple endeavour, still today we all are working towards the successful commercialisation of a perfectly behaving battery in the field," Shrivastava wrote. That sentence is the culture. People who stay are the ones who read it and reach for the keyboard.
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