Website:
kensara.in
Job details:
Company Description Kensara.ai is an AI-native compliance firm focused exclusively on India’s Digital Personal Data Protection Act (DPDPA), helping businesses shift from manual, uncertain processes to clear, continuous, and auditable compliance. The company combines autonomous AI agents with experienced privacy professionals to deliver end-to-end DPDPA support, including data mapping, consent and rights management, DPIAs, policy creation, vendor assessments, breach readiness, and ongoing monitoring. Kensara.ai serves Indian startups, SMEs, and larger enterprises that need fast, reliable, and affordable compliance without relying on spreadsheets or fragmented tools. Its platform provides leadership teams with real-time visibility into compliance status and an operational system of record for data protection, making it especially valuable to digital-first and AI-first companies in sectors such as SaaS, fintech, healthtech, and marketplaces. Kensara.ai’s mission is to make DPDPA compliance faster, clearer, and more trustworthy, enabling organizations to scale with confidence.
Role Description The Formal Verification Researcher will work on designing, analyzing, and implementing formal methods to verify the correctness and compliance of systems related to data protection and AI-driven workflows. This full-time, on-site role is based in Indore and involves developing formal models, specifying properties, and using verification tools to ensure systems meet DPDPA and internal security and reliability requirements. Day-to-day responsibilities include conducting theoretical and applied research in formal verification, collaborating with engineering and compliance teams to translate legal and policy requirements into formal specifications, and prototyping tools or frameworks that support automated verification. The researcher will review system architectures and codebases to identify potential correctness and compliance gaps, document findings and proofs, and present results to technical and non-technical stakeholders. The role also includes staying current with advances in formal methods, privacy engineering, and AI safety, and contributing to publications, internal knowledge bases, and best practices.
Qualifications
- Strong foundation in formal methods, including experience with model checking, theorem proving, or static analysis tools (e.g., Coq, Isabelle, HOL, Z3, TLA+, NuSMV, or similar).
- Solid background in theoretical computer science, logic, or mathematics, with the ability to design and reason about formal specifications, proofs, and correctness properties.
- Proficiency in at least one programming language commonly used in research or systems development (such as Python, OCaml, Haskell, Rust, or C/C++), and familiarity with software engineering practices.
- Experience or strong interest in data protection, privacy engineering, security protocols, or compliance-related systems, ideally with exposure to regulatory frameworks such as DPDPA or GDPR.
- Ability to collaborate in interdisciplinary teams, communicate complex technical concepts to diverse audiences, and produce clear research reports
Click on Apply to know more.
