Engineering Manager - Fullstack AI Technologies at Recruiting Bond · Mumbai, Navi Mumbai · 10 - 15 years · ₹55L - ₹80L / yr · Bootstrapped · Posted 22 Mar 2026

Location: Mumbai, Maharashtra, India
Sector: Technology, Information & Media
Company Size: 500 - 1,000 Employees
Employment: Full-Time, Permanent
Experience: 10 - 14 Years (Engineering Leadership)
Level: Engineering Manager / Group EM
ABOUT THIS MANDATE :
Recruiting Bond has been exclusively retained by one of India's most prominent and well-established digital platform organisations operating at the intersection of Technology, Information, and Media to identify and place an exceptional Engineering Manager who can lead engineering teams through an enterprise-wide AI adoption and digital transformation agenda.
This is a high-impact, hands-on leadership role at the nexus of people, product, and technology. The organisation is executing one of the most ambitious AI transformation programmes in its sector and this Engineering Manager will be a core driver of that change. You will lead multiple squads, own engineering delivery end-to-end, embed AI tooling and practices into the team's DNA, and shape the engineering culture of tomorrow.
We are seeking leaders who code when it matters, who build systems and teams with equal conviction, and who view AI not as a trend but as a fundamental shift in how great software is built.
THE OPPORTUNITY AT A GLANCE :
AI-First Engineering Culture :
- Own AI adoption across your squads - from LLM tooling integration to automation-first delivery workflows. Make AI a default, not an afterthought.
Hands-On Engineering Leadership :
- Stay close to the code. Lead architecture reviews, unblock engineers, and set the technical bar - not just the management agenda.
People & Org Builder :
- Grow engineers into leaders. Build squads of 615 across functions. Drive hiring, career frameworks, and a culture of psychological safety.
KEY RESPONSIBILITIES :
1. Hands-On Technical Engagement :
- Remain deeply embedded in the technical work participate in design reviews, architecture decisions, and critical code reviews
- Set and uphold the engineering quality bar : performance benchmarks, security standards, test coverage, and release quality
- Provide technical direction on backend platform strategy, API design, service decomposition, and data architecture
- Identify and resolve systemic technical debt and architectural risks across team-owned services
- Unblock engineers by diving into complex problems debugging, pair programming, and system analysis when it matters
- Own key technical decisions in collaboration with Tech Leads and Principal Engineers; balance pragmatism with long-term sustainability
2. AI Adoption, Integration & Transformation (2026 Mandate) :
- Define and execute the team's AI adoption roadmap - from developer tooling to product-facing AI features
- Champion the integration of GenAI tools (GitHub Copilot, Cursor, Claude, ChatGPT) across the full engineering workflow coding, testing, documentation, incident response
- Embed LLM-powered capabilities into the product : recommendation engines, intelligent search, conversational interfaces, content generation, and predictive systems
- Lead evaluation and adoption of AI-assisted SDLC practices : automated code review, AI-generated test suites, intelligent observability, and anomaly detection
- Partner with Data Science and ML Platform teams to productionise ML models with robust MLOps pipelines
- Build team literacy in prompt engineering, RAG (Retrieval-Augmented Generation), and AI agent frameworks
- Create an experimentation culture : run structured AI pilots, measure productivity impact, and scale what works
- Stay ahead of the AI tooling landscape and advise senior leadership on strategic AI investments and engineering implications
3. People Leadership & Team Development :
- Lead, manage, and grow squads of 6 - 15 engineers across seniority levels (L2 through L6 / Junior through Staff)
- Conduct structured 1 : 1s, career growth conversations, and development planning with every direct report
- Design and execute personalised AI upskilling programmes ensure every engineer develops practical AI fluency by end of 2026
- Build and maintain a high-performance team culture : clarity of ownership, accountability, fast feedback loops, and psychological safety
- Drive performance management fairly and rigorously recognise top performers, manage underperformance constructively
- Lead technical hiring end-to-end : define job requirements, conduct bar-raising interviews, and make data-driven hire decisions
- Contribute to engineering career frameworks and level definitions in partnership with the VP / Director of Engineering
4. Engineering Delivery & Execution Excellence :
- Own end-to-end delivery for multiple product squads from planning and scoping through production release and post-launch stability
- Implement and refine agile delivery frameworks (Scrum, Kanban, Shape Up) calibrated to squad needs and product cadence
- Drive predictable delivery : maintain healthy sprint velocity, manage WIP limits, and ensure dependency resolution across teams.
- Establish and own engineering KPIs : DORA metrics (deployment frequency, lead time, MTTR, change failure rate), uptime SLOs, and velocity trends
- Lead incident management : build blameless post-mortem culture, own RCA processes, and drive systemic reliability improvements
- Balance technical debt repayment with feature velocity negotiate prioritisation transparently with Product leadership
5. Strategic Leadership & Cross-Functional Influence :
- Serve as the primary engineering partner for Product, Design, Data, and Business stakeholders translate ambiguity into executable engineering plans
- Participate in quarterly roadmap planning, capacity forecasting, and OKR definition for engineering teams
- Represent engineering in leadership forums articulate technical constraints, risks, and opportunities in business terms
- Contribute to org-wide engineering strategy : platform investments, build-vs-buy decisions, and shared infrastructure priorities
- Build relationships across geographies (Mumbai HQ + distributed teams) to maintain alignment and delivery cohesion
- Act as a culture carrier and ambassador for engineering excellence, innovation, and responsible AI use
AI TRANSFORMATION LEADERSHIP 2026 EXPECTATIONS :
In 2026, Engineering Managers at this organisation are expected to be active architects of AI transformation not passive observers. The following outlines the specific AI leadership expectations for this role :
AI Developer Productivity
- Drive measurable uplift in developer velocity through AI tooling adoption. Target : 30%+ reduction in code review cycle time and 40%+ increase in test coverage automation by Q3 2026.
LLM & GenAI Product Features
- Own delivery of GenAI-powered product capabilities : intelligent content, semantic search, personalisation, and conversational UX in production, at scale.
AI-Augmented Observability
- Implement AI-driven monitoring and anomaly detection pipelines. Reduce MTTR by leveraging predictive alerting, intelligent runbooks, and auto-remediation scripts.
Team AI Fluency :
- Build mandatory AI literacy across all engineering levels.
- Every engineer understands prompt engineering basics, AI ethics guardrails, and responsible AI deployment practices.
Responsible AI Governance :
- Partner with Security, Legal, and Data Privacy to ensure all AI deployments meet compliance standards, bias mitigation requirements, and explainability benchmarks.
TECHNOLOGY STACK & DOMAIN FAMILIARITY REQUIRED :
- Languages: Java/ Go/ Python/ Node.js /PHP /Rust (must be hands-on in at least 2)
- Cloud: AWS / GCP / Azure (multi-cloud exposure strongly preferred)
- AI & GenAI: OpenAI / Anthropic / Gemini APIs /LangChain /LlamaIndex / RAG / Vector DBs / GitHub
- Copilot: Cursor /Hugging Face
- Containers: Docker /Kubernetes /Helm /Service Mesh (Istio / Linkerd)
- Databases: PostgreSQL /MongoDB / Redis / Cassandra / Elasticsearch / Pinecone (Vector DB)
- Messaging: Apache Kafka /RabbitMQ /AWS SQS/SNS /Google Pub/Sub
- MLOps & DataOps: MLflow /Kubeflow / SageMaker / Vertex AI /Airflow /dbt
- Observability: Datadog /Prometheus /Grafana /OpenTelemetry / Jaeger /ELK Stack
- CI/CD & IaC: GitHub Actions ArgoCD / Jenkins / Terraform /Ansible /Backstage (IDP)
QUALIFICATIONS & CANDIDATE PROFILE :
Education :
- B.E. / B.Tech or M.E. / M.Tech from a Tier-I or Tier-II Institution - CS, IS, ECE, AI/ML streams strongly preferred
- Demonstrated engineering depth and leadership impact may complement institution pedigree
Experience :
- 10 to 14 years of progressive engineering experience, with at least 3 years in a formal Engineering Manager or equivalent people-leadership role
- Proven track record of managing and scaling engineering teams (615+ engineers) in a fast-growing SaaS or digital product environment
- Hands-on backend engineering background must be able to read, write, and critique production code
- Direct experience driving AI/ML feature delivery or AI tooling adoption within engineering organisations
- Exposure across start-up, mid-size, and large-scale product organisations, preferred adaptability is a core requirement
- Strong CS fundamentals: distributed systems, algorithms, system design, and software architecture
- Demonstrated career stability minimum of 2 years of average tenure per organisation.
The Ideal Engineering Manager in 2026 :
- Leads with context, not control, empowers engineers while maintaining accountability and quality
- Is fluent in both people language and technical language, switches registers naturally with engineers and executives alike
- Sees AI as a force multiplier for the team, not a threat. Actively experiments with and advocates for AI tooling
- Measures success by team outcomes, not personal output. Takes pride in what the team ships, not what they build alone
- Creates feedback loops obsessively between product and engineering, between seniors and juniors, between metrics and decisions
- Has strong opinions, loosely held, brings conviction to discussions but updates on evidence
- Invests in engineering excellence as seriously as delivery velocity knows that quality and speed are not opposites
WHY THIS ROLE STANDS APART :
AI Transformation at Scale :
- Lead one of the most significant AI adoption programmes in India's digital media sector.
- Our decisions will shape how hundreds of engineers work in 2026 and beyond.
Hands-On & Strategic Balance :
- A rare EM role that actively encourages technical depth.
- Stay close to the code while owning the people agenda - the best of both worlds.
Established Platform, Real Scale :
- 5001,000 engineers, proven product-market fit, and the org maturity to execute.
- This is not a greenfield startup gamble it is a serious company with serious ambition.
Clear Leadership Growth Path :
- A visible, direct path toward Director / VP of Engineering.
- Senior leadership is invested in growing its next generation of technology executives.

About Recruiting Bond
About
Recruiting Bond is a global leader in Recruitment Process Outsourcing (RPO), Executive Search, Headhunting, Talent Mapping, and Workforce Consulting. Founded by Pavan B, we are on a mission to power businesses through transformative talent strategies that scale teams, accelerate innovation, and unlock human potential.
With a presence across 25+ industries—from IT, Healthcare, and FinTech to Gaming, BioTech, and Web3—we specialize in hiring that drives outcomes. Our domain expertise spans high-growth startups to Fortune 500 companies, delivering elite CXO and leadership talent, strategic workforce solutions, and inclusive hiring at scale.
We help businesses:
✔️ Hire the right leaders and builders
✔️ Scale globally with speed and precision
✔️ Build talent-first roadmaps from MVP to IPO
Whether you're launching, scaling, or transforming—Recruiting Bond is your strategic partner in talent.
🔹 Industries: Technology | Healthcare | FinTech | Retail | Manufacturing | EdTech | Crypto | Real Estate | Web3 | Logistics | Energy & more
🔹 Services: Executive Hiring | RPO | Talent Strategy | Workforce Design | Startup Consulting | Diversity Recruitment
📨 Let’s build the future—together: https://recruitingbond.c
Tech stack
Candid answers by the company
We help businesses:
✔️ Hire the right leaders and builders
✔️ Scale globally with speed and precision
✔️ Build talent-first roadmaps from MVP to IPO
Whether you're launching, scaling, or transforming—Recruiting Bond is your strategic partner in talent.
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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.
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.
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.

Required Experience: 10–15 years (with at least 3–5 years in leadership roles)
● 10–15 years of overall experience in backend engineering, with strong exposure to
Python and/or Golang.
● 3–5 years of experience managing engineering teams.
● Proven experience delivering large-scale, distributed systems in production
environments.
● Strong understanding of microservices, cloud-native architecture, and DevOps
practices.
● Hands-on background in backend engineering (able to guide teams technically, even
if not coding daily).
● Familiarity with CI/CD pipelines, observability, and performance optimization.
● Experience in financial services or high-transaction domains is a plus.
● Experience leading teams that have utilized AI-driven development practices (e.g.,
agentic coding, LLM integration) to improve productivity and innovation is a
significant advantage.
Skills
● Excellent leadership and people management abilities.
● Strong communication and stakeholder management skills.
● Ability to balance technical depth with business priorities.
● Problem-solving mindset with a focus on delivery and impact.
● Passion for building engineering culture and improving developer experience.
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
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
About the Role
We are seeking a hands-on Tech Lead to design, build, and integrate AI-driven systems that automate and enhance real-world business workflows. This is a high-impact role for someone who enjoys full-stack ownership — from backend AI architecture to frontend user experiences — and can align engineering decisions with measurable product outcomes.
You will begin as a strong individual contributor, independently architecting and deploying AI-powered solutions. As the product portfolio scales, you will lead a distributed team across India and Australia, acting as a System Integrator to align engineering, data, and AI contributions into cohesive production systems.
Example Project
Design and deploy a multi-agent AI system to automate critical stages of a company’s sales cycle, including:
- Generating client proposals using historical SharePoint data and CRM insights
- Summarizing meeting transcripts
- Drafting follow-up communications
- Feeding structured insights into dashboards and workflow tools
The solution will combine RAG pipelines, LLM reasoning, and React-based interfaces to deliver measurable productivity gains.
Key Responsibilities
- Architect and implement AI workflows using LLMs, vector databases, and automation frameworks
- Act as a System Integrator, coordinating deliverables across distributed engineering and AI teams
- Develop frontend interfaces using React/JavaScript to enable seamless human-AI collaboration
- Design APIs and microservices integrating AI systems with enterprise platforms (SharePoint, Teams, Databricks, Azure)
- Drive architecture decisions balancing scalability, performance, and security
- Collaborate with product managers, clients, and data teams to translate business use cases into production-ready systems
- Mentor junior engineers and evolve into a broader leadership role as the team grows
Ideal Candidate Profile
Experience Requirements
- 5+ years in full-stack development (Python backend + React/JavaScript frontend)
- Strong experience in API and microservice integration
- 2+ years leading technical teams and coordinating distributed engineering efforts
- 1+ year of hands-on AI project experience (LLMs, Transformers, LangChain, OpenAI/Azure AI frameworks)
- Prior experience in B2B SaaS environments, particularly in AI, automation, or enterprise productivity solutions
Technical Expertise
- Designing and implementing AI workflows including RAG pipelines, vector databases, and prompt orchestration
- Ensuring backend and AI systems are scalable, reliable, observable, and secure
- Familiarity with enterprise integrations (SharePoint, Teams, Databricks, Azure)
- Experience building production-grade AI systems within enterprise SaaS ecosystems
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).
Read This Before Anything Else
We have 6 developers who can ship. What we don't have is someone who turns that into a real engineering function: real architecture, real leverage, real AI-driven advantage. If that gap sounds like an opportunity rather than a headache, you're in the right place. If it sounds like a lot of undefined work with no playbook handed to you, this one probably isn't for you. That's completely okay. There are plenty of great roles that fit differently.
About CraftMyPlate
CraftMyPlate is Hyderabad's go-to platform for food experiences for micro-events: house parties, birthdays, office celebrations, festive gatherings, and more. We're building the operating system for how India discovers, customises, and orders food for smaller events. We're backed by established founders and investors, and we're funded and growing fast. The next phase of that growth runs through engineering.
Where We Stand
Some numbers, because they matter more than adjectives. Order volume has grown 50x in two years, and we're compounding at roughly 3x year over year, without giving up equity to fund it. That means the business runs on its own economics. The growth is real demand, not runway bought with dilution, and every efficient architectural decision this role makes directly protects that.
Most people size up an opportunity by asking what's going to change in ten years. The more useful question, and the one this company is built around, is what won't change. People will keep gathering. They'll keep celebrating, hosting, and marking festivals, in 10 years and in 20. That permanence is the bet. You're not building infrastructure for a trend cycle. You're building for a category that outlasts the current AI wave, the next funding round, and probably us too.
The Technical Reality
Here's an honest read of the engineering problem, not a sanitized version of it.
Event-driven commerce doesn't scale like typical e-commerce. Demand isn't smooth, it's spiky: weekends, festival calendars, and event dates create real load concentration, and each order is tied to a hard deadline that can't slip the way a shipped package can. That has direct architectural consequences: systems need to handle bursty, unpredictable traffic without paying for idle capacity the rest of the time, which is exactly why we're serverless-first on AWS rather than running a fixed fleet sized for peak.
Underneath that, every order touches multiple systems that have to stay consistent: kitchen and vendor fulfillment status, inventory across partners, payment gateway settlement, and refunds, often in real time and often across more than one vendor for a single event. Getting that consistency right across SQL and NoSQL stores, without it becoming a source of support tickets and manual reconciliation, is a real architecture problem, not a CRUD problem.
The AI-agent layer is the next lever, and it's a business lever as much as a technical one. Every workflow we can hand to a well-orchestrated agent instead of a new hire is a workflow that scales without adding headcount, which is exactly how a company grows 3x a year without diluting equity to fund the team behind it. That's why agent orchestration across multiple LLMs, using LangGraph, sits in the "go deep" tier of this role rather than being a nice-to-have.
You'll likely find some of this framing right and some of it worth challenging once you're actually in the codebase. That's expected, and honestly preferred over someone who just nods along.
Why This Role Exists
You'll be the most senior technical person in the company, reporting directly to the founder. Not a manager brought in to run standups. An owner. You set the architecture, you write code yourself, and you make the team materially better. You also own where AI and automation take this company next, starting with our first in-house AI agent product (details shared in the interview), and expanding from there into how the company runs, department by department: HR, finance, marketing, design, development, all sitting on an engineering layer that you design.
If you've outgrown a role where you plan but don't build, or where good ideas die in a committee, this is built to be the opposite of that.
What You'll Own
- Architecture, end to end. Scalable, cost-efficient systems from day one, not "fix it later" engineering. You own the decisions and their long-term consequences.
- Hands-on building. You are still writing code and shipping. This isn't a seat where you review other people's work all day. You lead by building.
- The engineering team. Directly manage, mentor, and level up our 6 developers. Build the technical bar, the review culture, and the calibration that lets the team ship independently.
- The AI-agent roadmap. Own the architecture behind our first AI agent product, then the broader strategy for AI agents and automation across every function in the company, with engineering as the layer underneath all of it.
- Team scaling. Build the next layer of leads under you so execution quality scales without you being the bottleneck.
- Technical accountability. When something breaks, you fix it. You don't escalate and wait.
Our Stack, and the Depth We Expect
Not everything on this list needs the same level of mastery. Some of it you need to own at an architectural level. The rest you need to be strong enough to build yourself, direct the team on, or delegate to AI agents with confidence.
Go deep here. This is where the real architecture decisions live, and where the business impact is highest:
- AWS, serverless first. You should be genuinely well versed in AWS application development, not just "have used AWS." You should be able to design and guide serverless architecture (Lambda, API Gateway, DynamoDB, Step Functions, and similar) as our default way of building, because our demand curve is spiky by nature and fixed infrastructure is money left on the table.
- TypeScript, our primary language across backend and frontend.
- Agent orchestration across multiple LLMs, using LangGraph. This is core to our AI roadmap and our path to scaling operations without scaling headcount. You own how it's architected, not just how it's used.
Working proficiency. Build it yourself, direct the team, or hand it to an AI agent and know if the output is right.
This Is You If
- You've built and shipped real production systems yourself, not just reviewed other people's architecture from a distance.
- You go deep wherever the problem is, and you're comfortable owning the exact stack described above, not just "full-stack" in the abstract.
- You've made engineers around you measurably better, whether or not you've held the title for it yet.
- You're already using AI coding tools and agents seriously, like Claude, Cursor, or similar tools, as part of how you build, not as something you tried once. We'll likely explore this together in the interview.
- You have a bias toward leverage over hours. You'd rather automate or systematize a problem than grind through it. But when something's live and needs to be done right, you see it through completely, with no half-finished work.
- You want to build something for years, not land somewhere comfortable. We'll know the difference from how you talk about your last three years.
This Might Not Be the Right Fit If
- You'd prefer a stable, well-defined role with clear boundaries and someone else making the calls. That's a fair thing to want, just not what this is.
- You'd rather receive direction than bring us architecture and AI strategy yourself.
- You haven't yet gotten hands-on with AI coding tools in your daily work.
- You're drawn more to the title than the work behind it.
If none of that sounds like you, we'd love to hear from you.
Requirements
- 5 to 7 years of experience in software engineering, with real ownership of architecture-level decisions, not just feature delivery.
- Prior experience leading or mentoring engineers, formally or informally.
- Tier-1 or Tier-1+ engineering college strongly preferred (IIT, BITS, top NIT tier, or equivalent). We'll consider other institutions only with clearly commendable, verifiable work: real systems you can walk us through in depth, strong open-source contributions, or a track record that speaks for itself. Pedigree is a proxy for speed, not a checkbox. We test for the underlying ability regardless.
- Comfortable in an early-stage environment: undefined problems, few processes, and the expectation that you help define both.
Compensation
Competitive, with equity. We're formalizing a structured ESOP program alongside this hire. Specific numbers are discussed directly in later interview rounds.
If reading this got you a little excited about what you'd build here, we'd genuinely love to talk. If it didn't quite land, no hard feelings. We just want the right fit for both sides.
Engineering Manager – Backend
Location: Flexible / Hybrid (Mon–Fri)
Website: https://www.solarsquare.in
About the Role
SolarSquare is building the infrastructure for India's clean energy transition. We're looking for an Engineering Manager who doesn't just run a team — someone who builds one from the ground up, makes consequential technical bets, and treats engineering outcomes as business outcomes.
You'll own the technical strategy and delivery for our full-stack platform, lead a growing team of SDE1–SDE3 engineers, and work directly with product, design, and business to shape what we build and how fast we build it. This is a role for someone who has operated in resource-constrained environments, shipped systems that held up under pressure, and left every team they've led measurably better than they found it.
If you've only ever executed someone else's roadmap, this isn't the right fit. If you've ever built something from scratch and felt personally responsible for whether it worked.
What You'll Own
Team & Culture
- Build, hire, and develop a high-performing full-stack engineering team including setting the bar for what "high-performing" means at SolarSquare
- Create genuine career growth paths for engineers.
- Maintain team health, retention, and motivation through periods of rapid change and ambiguity
Technical Strategy
- Define and drive the architectural roadmap
- Make and own technical bets: when to invest in platform, when to ship fast, when to pay down debt
- Establish observability, reliability, and security standards before they become production fires
Delivery
- Translate business goals into engineering priorities and push back when the translation is wrong
- Set clear goals, metrics, and delivery expectations; hold yourself and the team accountable to them
- Manage trade-offs between short-term product velocity and long-term engineering health
Cross-Functional Influence
- Partner with Product, Design, and Business stakeholders and influence decisions upstream.
- Communicate technical risk, cost, and complexity clearly to non-technical leadership
What We're Looking For
- 7–10 years of engineering experience, with at least 3 years leading teams.
- Strong understanding of distributed systems design: idempotency, retries, DLQs, circuit breakers, eventual consistency, you've had to debug these in production.
- Proven experience with event-driven architecture and Kafka including schema design, consumer group management, and failure recovery patterns.
- Comfort with relational (PostgreSQL) and NoSQL (MongoDB, Redis, ) databases including query optimisation and schema design decisions at scale.
- You've designed or operated systems handling meaningful traffic ideally 10K+ RPS. significant daily transaction volumes, or consumer-scale user bases (1M+ users)
- You understand what 99.99% uptime actually costs to maintain and you've made the infrastructure and on-call decisions to back it.
- You've written or enforced SLOs, SLAs, and incident management processes.
- You've done a postmortem that changed something real about how the team operates.
- Hands-on experience with AWS, GCP, or Azure beyond just deploying services, cost optimisation, right-sizing, architecture decisions that meaningfully reduced spend
- Working knowledge of containerisation (Docker) and orchestration (Kubernetes) enough to unblock your team.
- CI/CD pipeline ownership you've built or significantly improved a pipeline.
- Experience with observability tooling: Prometheus, Grafana, Datadog, ELK, or equivalent and more importantly, a philosophy about what to instrument and why
- You've made the call between monolith and microservices and you can defend it with context.
- You've managed technical debt consciously: triaged it, prioritised it, and made the case to stakeholders for when to pay it down
- You've navigated a hard conversation with a product or business stakeholder and changed the outcome
- Your engineers grow under you. You can point to people you've promoted, coached, or unblocked
- You know how to build alignment across functions where incentives don't naturally align
- You have clear examples of decisions you made under ambiguity and you can articulate the trade-offs you weighed
- You've identified a systemic problem and fixed it without being asked
- You've built or rebuilt something that wasn't working a team, a process, a system
Work Arrangement
Flexible work setup, including hybrid options. Monday to Friday. Learn more about us at https://www.solarsquare.in.





