Vice President — Engineering at 100 network · Bengaluru (Bangalore) · 14 - 15 years · ₹70L - ₹90L / yr · Posted 19 Sep 2026

About the role
You will be a pivotal member of the leadership team, responsible for driving the company's product and platform strategy while overseeing engineering excellence across AI, data, platform, DevOps and infrastructure. This is a mission-critical role for an engineering leader who is both strategic and hands-on, and who can build scalable technologies for global enterprise clients in a fast-paced innovation ecosystem.
Reports to: CEO · Location: Bengaluru, India — hybrid, 3 days a week in office
What you will do
Technology & product leadership
- Define and drive the technology vision, architecture and long-term platform roadmap.
- Oversee the architecture, design and delivery of highly scalable enterprise systems.
- Ensure engineering excellence, velocity and reliability across the product lifecycle.
Engineering & platform management
- Lead platform engineering, product technology, DevOps, infrastructure and Quality Engineering.
- Build robust cloud-native systems using the Azure, AWS and GCP ecosystems.
- Oversee operational effectiveness, including uptime, production reliability and cost optimisation.
Innovation & AI strategy
- Spearhead Mission AI by developing scalable, production-grade AI/ML and GenAI capabilities.
- Own the GenAI/LLM solutions architecture.
- Core specialisation in AI agents and autonomous workflows, data extraction and intelligent automation.
- Direct hands-on architectural oversight of large language models, applied AI and multi-layered deep learning products.
- Extensive expertise in building intelligent document automation systems — similar in complexity to patent parsing, legal workflow automation and structured decision intelligence tools.
Technical leadership
- A proven track record overseeing product architecture, tech strategy and cross-functional engineering execution across core full-stack and AI platforms.
- Collaborate with executive leadership on business strategy, client requirements and product delivery.
- Build, mentor and scale high-performing engineering teams with a growth mindset.
- Establish a strong technology culture grounded in ownership, innovation and continuous learning.
What success looks like
- Mission AI: build a world-class AI system leveraging GenAI, ML and enterprise-grade data engineering.
- Hyper-scaling: architect and scale the platform to match global industry leaders in the IP space.
- Culture building: develop a strong engineering organisation with high ownership, performance and innovation DNA.
Qualifications & experience
- Preferably under 15 years of enterprise software engineering experience across B2B SaaS or technology-first companies; fewer is fine for an exceptional engineer.
- A proven track record of taking early-stage AI/ML prototypes and scaling them into robust enterprise SaaS platforms featuring multi-agent orchestration, complex workflows and decision intelligence.
- Experienced in building and mentoring agile, lean startup teams of full-stack and machine learning engineers from the ground up.
- Proven leadership in defining and executing technology strategy and platform roadmaps.
- Extensive cloud-native engineering experience with Azure, AWS and GCP.
Technical expertise
- Strong full-stack engineering background (Java, Python, JavaScript frameworks).
- Expertise with JS frameworks such as React, Angular and Node.js.
- Experience building and scaling distributed systems and microservices.
- Strong knowledge of databases (SQL, NoSQL), data modelling and unstructured data management.
- Strong understanding of Agile methodologies and tools (Atlassian, Git, CI/CD pipelines).
Behavioural & leadership competencies
- Product and delivery management expertise, end to end, including delivery and customer support.
- Excellent communication, with the ability to influence executive stakeholders.
- High technical proficiency combined with strong business acumen.
- Strong analytical and decision-making skills.

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Title - Sr Engineering Manager
Location –Remote
EGNYTE YOUR CAREER. SPARK YOUR PASSION.
Egnyte is a place where we spark opportunities for amazing people. We believe that every role has meaning, and every Egnyter should be respected. With 22,000+ customers worldwide and growing, you can make an impact by protecting their valuable data. When joining Egnyte, you’re not just landing a new career, you become part of a team of Egnyters that are doers, thinkers, and collaborators who embrace and live by our values:
- Invested Relationships
- Fiscal Prudence
- Candid Conversations
ABOUT EGNYTE
Egnyte is the secure multi-cloud platform for content security and governance that enables organizations to better protect and collaborate on their most valuable content. Established in 2008, Egnyte has democratized cloud content security for more than 22,000 organizations, helping customers improve data security, maintain compliance, prevent and detect ransomware threats, and boost employee productivity on any app, any cloud, anywhere. For more information, visit www.egnyte.com
The Monetization Infrastructure team is responsible for all the systems that power Egnyte’s back office: billing, customer intake, account lifecycle and many others. This highly crucial function combines strong business attachment with technical complexity due to Egnyte’s scale and strong pace of innovation.
WHAT YOU’LL DO:
- Lead the Monetization Infrastructure engineering group, reporting to the Platform Engineering VP.
- Be hands-on and lead from the front; provide technical inputs and direction to the group, acting as a check and balance on key technical decisions and helping shape technical direction. Participate and contribute to system designs and code reviews.
- Ensure high quality operation of the systems under your responsibility. Drive a culture of ownership and continuous operational improvement.
- Collaborate with key stakeholders, such as Finance, Product Management and other Engineering groups, to implement end-to-end use cases and support high quality of service.
- Champion fluent use of AI tools across the team and drive adoption of advanced AI-assisted software development lifecycle (SDLC) practices.
YOUR QUALIFICATIONS:
- Managed engineering teams of 15+ people in SaaS product companies, including experience leading managers.
- Hands-on: understand and be able to contribute to system designs. Past background as a staff engineer or architect with a track record of releasing widely adopted solutions.
- Past background in Python (mandatory) and Java (desirable).
- Understanding of cloud platforms (GCP, Azure or AWS) and infrastructure as code concepts is highly desirable.
- Experience in leading distributed teams.
- Fluent in applying AI tools across the engineering workflow, with a track record of driving advanced AI-driven SDLC adoption within a team.
BENEFITS:
- Competitive salaries
- Company equity depending on role and level
- Medical insurance and healthcare benefits for you and your family
- Fully paid premiums for life insurance
- Flexible hours and PTO
- Gym reimbursement
- Childcare reimbursement
- Group term life insurance
Equal Employment Opportunity
At Egnyte, we celebrate our unique differences and thrive on our diversity for our employees, our products, our customers, our investors, and our communities. Our global Egnyte Employee Communities (EECs) support representation and inclusion across our diverse workplace. Egnyters are encouraged to bring their whole selves to work and to appreciate the many differences that collectively make Egnyte a higher-performing company and a great place to be.
Any employees with questions or concerns about equal employment opportunities in the workplace are encouraged to bring these issues to the attention of hrategnyte.com. Egnyte will not allow any form of retaliation against employees who raise issues of equal employment opportunity. If employees feel they have been subjected to any such retaliation, they should contact hrategnyte.com. To ensure the workplace is free of artificial barriers, violation of this policy including any improper retaliatory conduct will lead to discipline, up to and including discharge. All employees must cooperate with all investigations conducted pursuant to this policy.
Job Description: Lead - Cloud Engineering (AWS / Azure)
Role Title: Lead - Cloud Engineering
Experience Level: 10+ Years
Domain Focus: Healthcare AI & Cloud Infrastructure
Location: Remote
Job Overview
We are seeking an experienced Lead - Cloud Engineering with over 10 years of IT experience to lead our cloud strategy, architecture, and infrastructure teams. In this role, you will oversee end-to-end cloud deployment, multi-cloud migration, and scalable architecture designed to support cutting-edge Generative AI applications in the healthcare technology domain.
The ideal candidate brings deep technical expertise in both AWS and Azure, strong hands-on capability in cloud infrastructure, and proven leadership experience driving security, compliance, and team growth.
Key Responsibilities
Cloud Architecture & Migration
- Lead the architecture, design, and execution of cloud migrations, deployments, and modernizations across AWS and Azure environments.
- Drive Infrastructure as Code (IaC) standards using Terraform, CloudFormation, or Bicep to ensure scalable, automated infrastructure provisioning.
- Build high-availability, low-latency architectures optimized for data-intensive Generative AI and Machine Learning workloads.
Security & Healthcare Compliance
- Enforce healthcare security standards including HIPAA, HITRUST, SOC 2, and data governance best practices across all cloud assets.
- Implement Zero-Trust security, Identity Access Management (IAM), data encryption key management, and continuous vulnerability monitoring.
Leadership & Team Management
- Manage, mentor, and scale a high-performing team of DevOps, Cloud, and SRE Engineers.
- Drive Agile workflows, sprint planning, incident response frameworks, and SLA compliance.
- Collaborate closely with Data Engineering, AI/ML, and Software Product teams to align infrastructure with business roadmaps.
Operations & FinOps
- Establish cloud cost optimization strategies (FinOps) to manage computing costs associated with AI models and large-scale data processing.
- Manage monitoring, alerting, and telemetry frameworks (e.g., Prometheus, Datadog, CloudWatch) to ensure 99.99% uptime.
Key Requirements
- Experience: 10+ years of overall IT experience with at least 5+ years in a cloud leadership or lead architect role.
- Cloud Platforms: Advanced hands-on expertise with both AWS (e.g., EC2, S3, EKS, Bedrock, SageMaker) and Azure (e.g., AKS, Azure OpenAI, Blob, Virtual Machines).
- DevOps & IaC: Strong background in Terraform, Docker, Kubernetes, CI/CD pipelines (GitHub Actions, GitLab CI, or Jenkins).
- Domain Knowledge: Prior experience building or managing cloud environments within Healthcare, Life Sciences, or HealthTech is strongly preferred.
- AI/ML Familiarity: Experience supporting cloud infrastructure for machine learning pipelines, LLM deployments, or GPU compute management.
- Certifications (Preferred): AWS Certified Solutions Architect – Professional, Azure Solutions Architect Expert, or Certified Kubernetes Administrator (CKA).
Platform Engineering Lead (For client company)
Location: Pune, India
Experience: 7+ years
What Success Looks Like
- Engineering teams ship faster with confidence and built-in guardrails.
- Cloud cost, security, and reliability are predictable, measurable, and well-managed.
- CI/CD pipelines are trusted, standardized, and production-ready.
- Platform decisions reduce cognitive load instead of introducing unnecessary process.
Scope & Expectations
This is a hands-on leadership role combining architecture and implementation.
You will:
- Build, not just review.
- Own the platform roadmap—not just infrastructure tickets.
- Act as a force multiplier for product engineering teams rather than becoming a bottleneck.
- Drive platform strategy while remaining deeply involved in execution.
Key Responsibilities
Platform & Cloud Architecture
- Own Zoop's platform and cloud architecture across GCP and AWS.
- Design reusable, opinionated platform patterns instead of one-off infrastructure.
- Build and evolve Zoop's Internal Developer Platform (IDP), including:
- Self-service environments
- Golden paths (paved roads)
- Standardized templates
- Built-in engineering guardrails
- Lead Kubernetes and cloud-native adoption at scale.
- Drive infrastructure automation using Terraform, Pulumi, or similar Infrastructure-as-Code (IaC) tools.
CI/CD, Reliability & Developer Experience
- Establish robust CI/CD practices with quality gates and production readiness.
- Improve deployment safety through automation and testing.
- Define and monitor:
- Golden Signals
- SLIs
- SLOs
- Incident response processes
- Reduce operational toil and improve developer productivity.
- Make observability a first-class capability using cost-efficient monitoring systems.
- Build an observability platform that multiple engineering teams can easily integrate into their applications.
Security, Privacy & Compliance
- Build security-by-default into infrastructure and deployment pipelines.
- Lead implementation and continuous compliance for:
- DPDP Act (India)
- ISO 27001:2022
- SOC 2 Type II
- Implement:
- Zero Trust architecture
- Least-privilege access
- Secure data isolation
FinOps & Cloud Optimization
- Make cloud costs transparent and accountable across engineering teams.
- Establish FinOps practices including:
- Budgets
- Cost alerts
- Optimization routines
- Drive build-vs-buy decisions using clear ROI analysis.
AI, Data & MLOps Foundations
- Build secure and scalable foundations for AI and MLOps workloads.
- Define guardrails for AI systems and sensitive data handling.
Leadership & Collaboration
- Partner closely with engineering teams to align infrastructure strategy with product goals.
- Mentor engineers and guide teams through technical change.
- Balance long-term platform initiatives with practical execution.
What We're Looking For
Experience
- 7+ years of experience building and operating production infrastructure.
- Experience scaling engineering platforms in high-growth or regulated companies.
- Strong hands-on expertise in:
- Kubernetes and the cloud-native ecosystem
- Service Mesh technologies
- Policy Engines
- GCP, AWS (Azure exposure is a plus)
- Terraform and Infrastructure as Code
Engineering & Operations
- Strong understanding of SDLC and modern CI/CD systems (Jenkins, GitOps, etc.).
- Experience with observability tools such as:
- Grafana
- Prometheus
- New Relic
- Comfortable reading and contributing to production systems written in:
- Go
- Python
- Node.js
Security & Compliance
- Practical experience implementing ISO 27001 and SOC 2 controls.
- Strong understanding of:
- Data protection
- Privacy
- Identity and access management
- Security best practices
Mindset
We're looking for someone who is:
- Action-oriented with sound engineering judgment.
- Analytical, cost-conscious, and reliability-focused.
- Collaborative, calm under pressure, and open to feedback.
- Comfortable challenging decisions and explaining trade-offs when necessary.
Nice to Have
- Experience in fintech, identity, or other regulated industries.
- Built Internal Developer Platforms (IDPs) or shared infrastructure tooling.
- Contributions to open-source projects.
Key Responsibilities:
Team Leadership and Management:
- Lead, mentor, and manage a team of backend developers, fostering a culture of collaboration, innovation, and technical excellence.
- Promote a shared vision for the team, ensuring alignment with business goals and organizational objectives.
- Conduct performance reviews, provide constructive feedback, and create opportunities for team members’ professional growth.
- Drive cross-functional collaboration between development teams, designers, and product managers to deliver seamless and high-quality software.
Technical Strategy and Execution:
- Define and drive architectural decisions for both backend and frontend systems,ensuring scalability, reliability, and performance.
- Advocate and implement best practices in software development, including coding standards, test-driven development (TDD), and peer code reviews.
- Encourage the adoption of Large Language Models (LLMs) and AI-driven tools to optimize development and testing workflows.
- Provide technical direction on backend development using modern frameworks and languages, as well as frontend development using React, Angular, or Svelte.
Process and Quality Management:
- Ensure robust integration between backend APIs and frontend systems for seamless user experiences.
- Establish and enforce coding, testing, and deployment standards for both backend and frontend teams.
- Implement and optimize automated testing frameworks for backend and UI layers to ensure comprehensive coverage.
- Monitor system performance and application stability, proactively identifying and mitigating risks.
- Establish CI/CD pipelines and DevOps best practices for efficient and reliable delivery cycles.
Stakeholder Collaboration:
- Act as a bridge between engineering teams, business stakeholders, and leadership, ensuring effective communication and alignment.
- Translate complex business requirements into actionable technical solutions and guide teams through their implementation.
- Provide regular updates on progress, challenges, and innovations to stakeholders.
Innovation and Exploration:
- Stay updated on advancements in Large Language Models (LLMs) and integrate them into development and quality assurance workflows where applicable.
- Encourage the exploration of cutting-edge technologies, tools, and frameworks for both backend and frontend development.
- Champion the use of AI and machine learning tools for performance optimization, automated testing, and enhanced developer productivity.
Skills & Qualifications:
Must-Have Skills:
- Proven experience as an Engineering Manager or similar leadership role.
- Strong technical background in backend technologies (e.g., Java, Spring Framework).
- Deep understanding of RESTful API design, microservices architecture.
- Hands-on experience with containerization and orchestration tools like Docker.
- Solid knowledge of Agile methodologies, TDD, and CI/CD pipelines.
- Excellent leadership, communication, and problem-solving skills.
- Expertise in integrating Large Language Models (LLMs) and AI-powered tools into development workflows.
Nice-to-Have Skills:
- Experience with cloud platforms like AWS, GCP, or Azure.
- Knowledge of automated testing frameworks for both backend (e.g., JUnit, Postman) and frontend (e.g., Playwright).
- Understanding of DevOps practices and infrastructure-as-code tools like Terraform.
- Exposure to AI/ML frameworks and libraries for enhancing application features and team efficiency.
Staff Engineer - AI:
Location : India, Remote
Job Description
Egnyte is seeking an experienced Staff Software Engineer to join our Engineering department. The Engineering department builds large distributed components and services that run Egnyte's Cloud Platform. Our code serves billions of requests per day with sub-second latency in a fault-tolerant environment. We process and analyze millions of files and events daily. Some of the responsibilities for this department include Egnyte's Cloud File System, Content Classification, Content Lifecycle Management, User Behavior Analysis, Object Store, Metadata Stores, Search Systems, Recommendations Systems, Synchronization, and intelligent caching of multi-petabyte datasets. We are looking for candidates with a shared passion for building large-scale distributed systems and a keen sense for tackling complexities that come with scaling through multiple orders of magnitude.
In this role, you will (But are not limited to):
- Design and develop highly scalable and resilient cloud architecture that seamlessly integrates with on-premises systems
- Drive the team’s goals and technical direction to find and pursue technical opportunities that make Egnyte’s cloud platform more efficient
- Effectively communicate complex design and architecture details
- Understand company and industry-wide trends to help develop new technologies
- Conceptualize, develop, and implement changes that prevent key systems from becoming unreliable, under-utilized, or unsupported
- Own all aspects of critical software projects from design to implementation, QA, deployment, and monitoring
Qualifications
- BS, MS, or PhD. in Computer Science or related technical field, or equivalent practical experience
- 8-15 years of professional experience in engineering with a history of technical innovation
- Experience providing technical leadership to engineers
Bonus Qualifications (Good to Have)
- The breadth of knowledge across infrastructure domains, with the ability to reason about everything from data center machine software to database solutions to machine learning infrastructure to front-end web or mobile applications
- Demonstrated success in designing and developing large-scale, complex systems
- Expertise with multi-tenant, highly complex, cloud solutions; experience with Hybrid and/or on-premises solutions desired
About Egnyte
In a content critical age, Egnyte fuels business growth by enabling content-rich business processes, while also providing organizations with visibility and control over their content assets. Egnyte’s cloud-native content services platform leverages the industry’s leading content intelligence engine to deliver a simple, secure, and vendor-neutral foundation for managing enterprise content across business applications and storage repositories. More than 16,000 customers trust Egnyte to enhance employee productivity, automate data management, and reduce file-sharing cost and complexity. Investors include Google Ventures, Kleiner Perkins, Caufield & Byers, and Goldman Sachs. For more information, visit www.egnyte.com
Technical Architect – Product Engineering
Experience: 15+ Years
Location: Pune, India
Employment Type: Full-time
Desired Skills: Python, Technical Architecture, AWS, Microservices, SaaS / Multi-tenant Architecture, Kubernetes, System Design
About the Role
We are looking for a Senior Technical Architect to lead the architecture, design, and technical evolution of an enterprise SaaS product. This is a hands-on leadership role requiring deep technical expertise, strong product engineering experience, and the ability to build scalable, secure, and high-performance platforms.
The ideal candidate should be passionate about solving complex engineering problems, driving innovation, mentoring development teams, and effectively leveraging AI to accelerate software development.
Key Responsibilities
- Own the overall product architecture and technical roadmap.
- Design and build scalable, secure, and highly available enterprise applications.
- Lead the design and implementation of new product features from concept to production.
- Remain hands-on with coding and contribute to critical product components.
- Drive architecture reviews, code quality, performance optimization, and engineering best practices.
- Lead cloud architecture, security, scalability, and DevOps initiatives.
- Evaluate and adopt modern technologies to improve product capabilities and engineering efficiency.
- Leverage AI tools (ChatGPT, GitHub Copilot, Cursor, Claude, etc.) to accelerate software development, code reviews, testing, documentation, debugging, and productivity.
Required Skills & Qualifications
- 15+ years of software product engineering experience with at least 5 years in a Technical Architect role.
- Strong hands-on expertise in Python and modern backend frameworks.
- Deep experience with AWS services and cloud-native application architecture.
- Strong understanding of DevOps, CI/CD pipelines, Infrastructure as Code (Terraform/CloudFormation), Docker, Kubernetes, and container orchestration.
- Experience designing microservices, REST APIs, event-driven architectures, and distributed systems.
- Strong knowledge of SQL and NoSQL databases.
- Experience with scalable SaaS platforms, multi-tenant architectures, and secure application design.
- Excellent understanding of software design patterns, performance tuning, observability, and system reliability.
- Strong analytical, problem-solving, and decision-making skills.
🚀 We’re Hiring: CTO at Happiword.com
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Happiword.com is building a global book ecosystem where readers discover great books and authors reach the right audience.
We’re looking for a passionate CTO & technology leader who wants to build from the ground up, lead technology, explore AI, and help take Happiword to millions of readers and authors.
If you want to build something meaningful, ambitious, and potentially world-changing — join us.
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Happiword.com — Building the future of books.
We are looking for an Engineering Lead to own the entire technology stack — from onboarding and underwriting to disbursals, repayments, and collections — and to build the engineering function into something genuinely AI-native.
What You'll Own
● Full tech stack: backend, frontend, infrastructure, integrations, and data pipelines
● Real-time underwriting and decisioning systems
● LOS/LMS architecture — onboarding, disbursals, repayments, and collections
● Integrations with bureaus, KYC providers, account aggregators, and payment gateways
● Reconciliation systems — disbursement, repayment, and NACH reconciliation end-to-end
● AWS infrastructure: scaling, reliability, uptime, and cloud cost ownership ● Data infrastructure for the credit and risk team — feature pipelines, model serving, experiment infrastructure
● Engineering leadership: hiring, sprint planning, code reviews, and execution standards
● Compliance systems: RBI guidelines, DPDP, KYC/AML, e-NACH, e-sign
AI-Native Engineering
This is a core part of the role, not a bonus. You will build a machine-readable knowledge base of the entire codebase — architecture, data models, service contracts, coding standards, decision history — so that AI agents working on code have the context to produce accurate, consistent output. You will build skills for code review, developer onboarding, and recurring engineering workflows. You will build a code review pipeline where agents do the first pass on every pull request. The knowledge base and the skills improve over time as the team grows and the product evolves.
What We're Looking For
● 7+ years in software engineering, with at least 2 years leading teams or architecture
● Strong hands-on experience with Python, Django, and React Native
● Deep expertise in AWS and cloud-native architecture
● Experience with both SQL and NoSQL databases
● Strong understanding of distributed systems, microservices, and API design
● Experience owning reconciliation or payment flow infrastructure in a lending or payments context
● Prior experience in fintech / NBFC / digital lending — mandatory
● Strong understanding of the full loan lifecycle — mandatory
● You have used LLMs seriously as engineering tools and have strong opinions about what makes AI-assisted development produce good output versus mediocre output
Bonus: Kubernetes / Kafka, AI/ML-driven underwriting, Account Aggregator framework, e-NACH / e-Sign / Video KYC integrations
What Success Looks Like
● scales with strong uptime, performance, and reliability
● Reconciliation runs cleanly — no financial discrepancies surface late ● A new engineer joins and is writing standard, correct code within their first week
● The credit team is never blocked on an engineering dependency
● Engineering health metrics are tracked and visibly improving
● AI agents are doing the structured first pass on code reviews, and the system gets smarter over time
Role & Responsibilities
Responsibilities
• Business: Immerse in operations until you think like an insider.
Rapidly acquire domain expertise through direct observation, translate between business and engineering seamlessly, and mentor engineers in your area on immersion. Influence senior stakeholders effectively, manage complex stakeholder landscapes with competing agendas, and build trust rapidly with new stakeholders.
• Delivery: Lead rapid delivery initiatives across teams in your area, coach on prototype-first approaches, and establish trust through consistent fast delivery. Build complete applications rapidly across any technology stack, select the right tools for each problem, and define clear criteria for prototype-to-production transitions.
• Generative AI: Architect RAG systems for complex use cases across teams, implement advanced techniques (hybrid search, reranking, query expansion), mentor engineers on RAG best practices, and establish RAG standards. Lead evaluation strategy across teams, establishing annotation guidelines, training human-calibrated LLM judges, and building evaluation pipelines that connect tracing to datasets to experiments.
• People: Build high-performing teams across your area, navigate complex interpersonal dynamics, foster psychological safety, and create environments where diverse perspectives are valued. Influence through communication at all levels — from frontline to executive. Handle difficult conversations skilfully and train engineers in your area on effective communication.
• AI-Augmented Development: Optimise AI tool usage across teams in your area, train engineers on AI-augmented and agentic engineering workflows, evaluate new AI development tools, and establish practices that balance AI speed with verification rigour.
• Scale: Design complex multi-component systems end-to-end, evaluate architectural options for large initiatives across teams, guide technical decisions for your area, and mentor engineers on architecture. Create debt reduction strategies across teams, influence roadmap decisions to include debt work, and teach engineers when to accept debt for speed versus when to invest in quality.
• Documentation: Define documentation standards across teams in your area, create documentation systems and templates, train engineers on spec-driven development, and ensure documentation quality across projects. Lead pattern generalization initiatives, defining criteria for when to generalize versus keep custom.
• Reliability: Define reliability standards across teams in your area, drive post-incident improvements systematically, design capacity planning processes, andmentor engineers on SRE practices.
Ideal Candidate
- Strong Staff Software Engineer / FDE profile (full-stack + production GenAI, multi-team technical leadership)
- Mandatory (Experience 1) – Must have 7+ years of relevant professional software engineering experience, with demonstrated full-stack delivery across backend and frontend.
- Mandatory (Experience 2) – Must have deep production experience with Python AND JavaScript/TypeScript, working comfortably across the full stack.
- Mandatory (Experience 3) – Must have 2+ years of experience in generative AI applications developement — LLM integrations, vector databases, RAG systems, and evaluation pipelines
- Mandatory (Experience 4) – Must have strong experience with modern frontend frameworks (Next.js / React) and backend API development.
- Mandatory (Experience 5) – Must have extensive experience with cloud platforms (AWS preferred; Azure/GCP valued), including infrastructure-as-code (CloudFormation / Terraform).
- Mandatory (Experience 6) – Must have working knowledge of multiple database paradigms — relational (PostgreSQL), document, and key-value (Redis) — with ability to select the right storage per problem.
- Mandatory (Experience 7) – Must have strong experience with CI/CD pipelines (e.g. GitHub Actions), containerization, and production deployment strategies.
- Mandatory (Experience 8) – Must have demonstrable fluency with AI coding tools (Claude Code, Cursor, GitHub Copilot, or similar) and proven ability to design agentic engineering workflows and train teams on them
- Preferred (Experience) – Advanced RAG techniques — hybrid search, reranking, query expansion — and establishing RAG standards across teams
Job Title: Vice President – Technology (VP Tech)
Company: Timble Technologies Pvt. Ltd
Location: Arjan Garh, New Delhi (On-site)
Experience: 15+ Years
About Timble AI
Timble Glance is a high-growth AI-powered RegTech and enterprise B2B SaaS platform delivering mission-critical solutions to the BFSI sector. Our infrastructure powers 30+ enterprise-grade APIs handling digital identity management, real-time fraud mitigation, automated compliance, and document intelligence. We engineer high-concurrency, resilient systems designed for extreme throughput, sub-second latency, and bank-grade data security.
Role Overview
As the Vice President – Technology, you will be the chief technical strategist and engineering executive driving Timble AI’s technical vision, platform modernization, and AI innovation. You will own the end-to-end architectural roadmap, lead cross-functional engineering pods, and scale high-volume distributed systems that safeguard critical financial data. This role requires an executive who combines boardroom strategic gravitas with deep hands-on engineering credibility, capable of bridging rapid B2B SaaS product iteration with rigorous BFSI regulatory standards.
Key Responsibilities
· Technology Vision & Architectural Strategy: Define and execute a multi-year engineering roadmap across core product suites (Identity Verification, Fraud Detection Engines, and Document Intelligence), balancing cutting-edge feature delivery with enterprise-grade stability.
· Large-Scale Platform Engineering: Oversee the architecture and performance of 30+ high-scale APIs, ensuring 99.9% uptime, sub-second latency, fault-tolerant concurrency, and strict "efficiency by design" across multi-tenant cloud environments.
· AI/ML & Intelligent Engineering: Drive the productionization of proprietary AI/ML and Generative AI pipelines—moving capabilities from experimental R&D into secure, low-latency, scalable BFSI workflows while advancing patent-pending intellectual property (IP).
· Cloud Architecture & FinOps: Direct cloud economics and infrastructure investments across AWS and GCP, establishing containerization, microservice modularity, automated CI/CD pipelines, and robust disaster recovery frameworks.
· Information Security & Regulatory Compliance: Enforce bank-grade security protocols, data privacy governance, and industry-mandated regulatory compliance (ISO 27001, SOC2, RBI/BFSI data localization guidelines) to protect sensitive enterprise data.
· People & Engineering Culture Leadership: Attract, mentor, and scale a world-class engineering organization (from SDE-1 to Principal Architects and Engineering Managers); institute rigorous code reviews, automated testing benchmarks, and clear career ladders.
· Executive & Stakeholder Alignment: Partner directly with the Founder, C-suite, and Product Leadership to translate complex technological initiatives into clear business outcomes, enterprise client trust, and scalable revenue growth.
Required Qualifications & Experience
· Experience: 15+ years of progressive software engineering and technology leadership experience, with significant tenure leading engineering organizations in Fintech, RegTech, or high-scale B2B SaaS.
· Education: B.Tech / M.Tech in Computer Science or related engineering field—Tier-1 institutes (IIT, IIIT, NIT) strongly preferred.
· Core Technical Mastery: Deep hands-on expertise in no, distributed system design, microservices, asynchronous architectures, API gateways, and relational/NoSQL database engines (PostgreSQL, Redis, MongoDB).
· Cloud & Infrastructure Rigor: Proven track record architecting enterprise systems on AWS/GCP, utilizing Docker, Kubernetes, Kafka/RabbitMQ, and modern APM/observability stacks.
· AI Production Track Record: Demonstrated experience successfully deploying, monitoring, and scaling machine learning, computer vision, or NLP/LLM models in latency-critical production environments.
· Governance & Delivery: Strong command of modern engineering methodologies (Agile, DevSecOps, TOGAF/ITIL principles) with a proven history of managing high-throughput, zero-downtime platforms.
Leadership Attributes
· Technically Credible Executive: Capable of engaging in deep-dive architectural RFCs with engineering teams while articulating business impact and ROI to board members and enterprise BFSI clients.
· Builder Mindset: Thrives in high-ownership, agile environments, successfully balancing rapid product velocity with uncompromised software quality and data integrity.
· Force Multiplier: Focuses on institutionalizing robust engineering practices and developing leadership pipelines rather than relying on individual heroics.
· You can visit our website .












