Engineering Manager at Jumio · Remote only · 10 - 20 years · ₹50L - ₹90L / yr · Remote only · Posted 17 Sep 2026

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.

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About Us
We're building the next generation of AI-powered business software. Our Chatbot application brings AI directly into customer and business workflows, combining a robust backend with LLM-powered agents to get real work done through conversation.
This is a chance to work on hard problems in backend systems, LLM agents, and orchestration — building zero-to-one, owning your area end-to-end, and shipping to production at scale.
Note: This is a customer-facing role, and strong communication skills are essential.
About the Role
We're looking for a Lead Software Engineer to help build and scale the backend and AI capabilities of our Chatbot application. This is a backend-heavy role for someone who can design robust, production-grade systems in Java while also bringing hands-on experience building LLM agents and orchestration layers that power intelligent conversational experiences.
What You'll Do
- Design, build, and scale backend services in Java that power the Chatbot application
- Build and integrate LLM-powered agents into the chatbot, including agent orchestration, tool use, and multi-step reasoning workflows
- Own features end-to-end — from architecture and design through implementation, testing, deployment, and iteration
- Drive technical decisions on system architecture, reliability, performance, and scalability for a backend serving real-time conversational workloads
- Lead by example — set engineering standards, review designs and code, and mentor engineers on the team
- Collaborate closely with product, design, and AI/ML teams to translate business requirements into shipped functionality
- Work directly with customers to understand real-world use cases, troubleshoot issues, and gather feedback to inform the roadmap
- Continuously improve the chatbot's conversational quality, reliability, and response accuracy
What We're Looking For
- 4–6 years of backend engineering experience, with strong, hands-on expertise in Java
- Practical experience building LLM-powered agents and agent orchestration in production systems
- Solid understanding of LLM fundamentals — prompting, tool use, reasoning, and evaluation
- Strong experience designing and building scalable, production-grade backend systems and APIs
- Ability to take technical ownership and lead design/architecture decisions with minimal oversight
- Comfort working in a fast-moving, high-ownership environment, balancing hands-on coding with technical leadership
- Excellent communication skills — this is a customer-facing role, and you'll regularly engage directly with customers to understand needs and explain technical solutions
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.
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
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.
Senior Full Stack Engineer (4 to 8 years)
About RunLoyal
RunLoyal is a fast-growing vertical SaaS and payments company headquartered in Atlanta, GA, building the operating system for the pet care industry — boarding, daycare, grooming, training, and dog parks. Our platform runs the daily operations of hundreds of real businesses, and our 2026 focus is scaling the product engine behind an expanding enterprise segment.
We're hiring a Senior Full Stack Engineer to lead our most strategic builds.
The Role
This is not a sprint-pool position. You'll operate the way forward-deployed engineers do — dropped into a problem space and trusted to drive it from ambiguity to shipped. You'll be handed a strategic initiative (a new AI product build, a greenfield module, a flagship platform project), gather context directly from stakeholders and customers, set the technical direction, structure the work, and deliver with teammates — leading from the front.
You'll report to the Head of Engineering and work embedded with the Head of Product on new initiatives, in an independent lane with direct access to leadership. We operate AI-native: our newest product surfaces are being designed and built with agentic AI workflows at the core, and you'll help define how AI-native engineering works here — not just follow a playbook.
Honest framing: we're a fast-moving, founder-driven team in transition toward modern SaaS delivery practice. You'll have real autonomy and real accountability in equal measure. If you need a fully paved road, this isn't your role. If you've shipped meaningful things through ambiguity before — and enjoyed it — read on.
What You'll Own
1. Strategic build projects — end-to-end
Own flagship initiatives from first principles to production: architecture, delivery plan, execution with teammates, release, and post-release iteration. You're accountable for the outcome, not just the code — which means demoing early, cutting scope intelligently, and shipping working software on a rhythm.
2. Technical leadership from the front
Set the technical direction on your projects and bring teammates along through visible working practice — pairing, reviewing, and raising the bar rather than issuing instructions. Mentor by doing. Contribute to system design and architecture decisions across the platform, and push our engineering practices forward.
3. AI-augmented delivery — our default operating mode
Independently architect and deliver full projects using AI-augmented workflows: agentic coding (Claude Code or equivalent), spec-driven development, AI-led test generation, and structured context management. This is how the role works day-to-day, not an accelerator bolted on. You'll co-author our internal AI engineering playbooks and raise the bar for how the whole team builds.
4. Core engineering
Design and ship scalable Spring Boot microservices, RESTful APIs, and responsive frontends in Angular or React. Write efficient SQL, optimize JVM performance, own production issues on your surfaces end-to-end, and leave the codebase better documented than you found it.
Leadership & Agency — what we'll evaluate hardest
- You lead from the front. You've set direction on projects and carried teammates with you — through working code and clear communication, not title or authority
- High agency. You identify what's blocking the outcome and remove it yourself — whether it's code, process, or a conversation someone needs to have
- Strong stakeholder muscle. You communicate clearly upward and outward — written updates, proactive demos, and comfort presenting to leadership and customers directly
- Async-native. You work effectively across time zones with documentation and over-communication as defaults, not afterthoughts
- Calm ownership under ambiguity. Handed a loosely defined problem, you structure it, sequence it, and start shipping
What You Bring
Must have
- Significant professional software development experience with real ownership scar tissue — you've led projects, not just tickets. We care about evidence, not years
- Strong hands-on Java and Spring Boot; solid microservices architecture and REST API design
- Frontend experience with Angular or React
- Experience with relational databases (MySQL/PostgreSQL) and SQL optimization; JVM fundamentals and backend performance
- AI-native engineering (hard requirement). You already deliver work through AI-augmented workflows — agentic coding tools, prompt/context engineering, AI-driven testing — and can demonstrate the most complex thing you've shipped this way
- Product-company experience: you've built for end users with daily stakes, and you think in outcomes
- Strong debugging, analytical, and problem-solving skills; unit testing and code coverage discipline
- Bachelor's degree in Computer Science or equivalent practical experience
Nice to have
- Forward-deployed, consulting, or founding-engineer experience — dropped into a customer or problem space and shipped
- AWS (EC2, ECS), Docker, CI/CD pipelines, Redis or similar caching
- SaaS or multi-tenant systems; Golang exposure
- DevOps and security best practices awareness
What You'll Gain
- Ownership of flagship builds on a live, growing SaaS platform — your projects, your outcomes, visible to the whole company
- Direct working partnership with the Head of Product and Head of Engineering
- A defining role in how AI-native engineering is practiced at a product company that takes it seriously
- Fast growth in a high-velocity startup with a clear product vision
How to Apply
Send the following — applications without all three will not be reviewed:
- Your project story. One page or less: a project you led end-to-end through significant ambiguity — what you shipped, how you led the team, and what measurably changed. Specifics over adjectives.
- Your AI workflow. A short description of how AI is embedded in your actual engineering workflow today — tools, techniques, and the most complex thing you've shipped with it.
- Your resume.

Role: Senior Software Developer – SDE3
Experience: 8-12 Years
Employment Type: Full-time
Location: Pune (Hybrid)
Job Description
We are seeking a highly skilled Senior Full-Stack Developer to design, develop, and deliver scalable, high-quality digital solutions. The ideal candidate combines deep expertise in modern microservices architecture, cloud platforms, and end-to-end feature delivery, with proficiency in agentic software development and a strong focus on engineering excellence, collaboration, and continuous innovation.
Responsibilities:
• Design and develop scalable, resilient applications using microservices architecture.
• Build end-to-end full-stack features, covering UI (React, TypeScript, Redux) and backend services.
• Develop Java (17+) / Spring Boot (3.x) microservices using Domain-Driven Design (DDD) and OpenAPI 3.x specifications.
• Implement event-driven architectures using Kafka, including topic design, consumer groups, and reliable message processing.
• Design optimized database schemas, write advanced SQL queries, and manage migrations using Liquibase within CI/CD pipelines.
• Lead low-level design (LLD) and define REST API and event contracts aligned with enterprise architecture standards.
• Conduct code reviews, enforce coding standards, and ensure high quality using SonarQube gates.
• Ensure high test coverage (>90%) using JUnit, Mockito, Testcontainers, Cucumber, Jest, and React Testing Library.
• Collaborate within Agile teams, mentor developers, and drive timely delivery of high-quality solutions.
• Leverage AWS, Docker, Kubernetes, CI/CD pipelines to improve productivity and system performance.
• Leverage AI-driven software engineering practices, including LLM-powered development tools, agentic AI workflows, code generation, automated testing, and AI-assisted debugging, to improve developer productivity, software quality, and delivery efficiency.
Required Qualification:
• Bachelor’s or Master’s degree in computer science, Information Technology, or a related field.
• Minimum 8 years of professional experience, including at least 5 years in full-stack development.
• Hands-on experience with microservices-based architecture and distributed systems.
• Strong understanding of functional programming, design patterns, and software architecture principles.
• Experience working in cloud environments (preferably AWS).
• Proficiency with CI/CD pipelines, Docker, and Kubernetes.
• Strong analytical thinking and problem-solving capabilities.
Must-Have Skills
• Strong proficiency in React.js, including Hooks, TypeScript, and state management using Redux Toolkit or React Query, along with testing frameworks such as Jest and React Testing Library.
• Extensive experience with Java 17+, Spring Boot 3.x, and the Spring ecosystem (Spring Cloud, Spring Security with OAuth 2.0), along with JPA/Hibernate.
• Hands-on experience with Apache Kafka, including topic design and managing consumer groups for event-driven architectures.
• Solid expertise in PostgreSQL, including schema design, performance tuning, indexing strategies, and database migration management using Liquibase.
• Proficiency in AI-assisted and agentic software development practices, with hands-on experience using AI coding assistants, autonomous development agents, and AI-enabled testing and code quality tools.
Good-to-Have Skills
• Experience with Redis, GraphQL, and AWS cloud services.
• Familiarity with AI-assisted development tools such as GitHub Copilot.
• Exposure to monitoring and observability tools like Kibana/ELK stack, Grafana, Glowroot, or Datadog.
• Experience working with modern development environments and IDEs (e.g., Kiro IDE).
We are looking for a hands-on Engineering Lead who can own backend engineering, DevOps, and delivery management.
This is not a coordination-only role. You will contribute technically while establishing the processes, accountability, and
operating rhythm needed for predictable delivery. You will manage multiple engineers and effectively use AI coding
agents and automation tools to improve the team's output without compromising quality.
Key Responsibilities
• Own the architecture, development, deployment, and reliability of our backend systems.
• Lead engineers through clear goals, task breakdowns, ownership, reviews, and regular feedback.
• Establish a process-oriented delivery system covering planning, estimation, execution, testing, release, and
retrospectives.
• Translate product requirements into technical plans, milestones, dependencies, and measurable deliverables.
• Track execution proactively, identify delivery risks early, and communicate status clearly.
• Remain hands-on with critical development, debugging, architecture, code reviews, and production issues.
• Own CI/CD, infrastructure, observability, deployment practices, and operational readiness.
• Improve engineering quality through coding standards, automated testing, documentation, and review processes.
• Delegate work effectively across team members according to their strengths and development needs.
• Use AI coding agents and engineering automation to parallelise suitable work, while reviewing and validating all
outputs.
• Build a culture of accountability in which work has clear owners, acceptance criteria, deadlines, and definitions of
done.
• Collaborate closely with product and business stakeholders to balance speed, scope, quality, and technical debt.
What We Are Looking For
• 6+ years of backend engineering experience.
• At least 2 years of experience leading or managing an engineering team.
• Strong hands-on backend development experience with Python, FastAPI, Django + Django REST Framework, and
PostgreSQL.
• Practical experience with cloud infrastructure (AWS), DevOps, CI/CD, containers (Docker), monitoring, and
production operations.
• Experience working in a mature, process-oriented engineering environment.
• Demonstrated ability to improve delivery predictability and engineering throughput.
• Strong understanding of agile planning, estimation, sprint execution, incident management, and retrospectives.
• Ability to manage multiple people and concurrent streams of work.
• Experience reviewing architecture, pull requests, test plans, and production-readiness requirements.
• Strong written and verbal communication skills.
• Ability to give direct, constructive feedback and hold team members accountable.
• Sound judgement about when to build, delegate, automate, or reduce scope.
Tech Stack
Must-have: Python, FastAPI, Django + Django REST Framework, PostgreSQL, SQLAlchemy (async) + asyncpg, Pydantic,
REST API design + JWT authentication, Docker, AWS (ECS, ALB, ECR, CloudWatch, S3, Secrets Manager), Git.
Strongly preferred: Redis, Elasticsearch / OpenSearch, WebSockets, Payment gateways (Razorpay / Cashfree), Third-
party / ERP integrations, CI/CD (AWS CodeBuild or GitHub Actions).
Nice-to-have: Frappe / ERPNext + MariaDB, Microservices architecture, PostHog / CleverTap / Firebase, B2B e-commerce
or order management experience.
AI-Assisted Engineering
The ideal candidate should be comfortable incorporating AI into the software-development lifecycle. This includes:
• Breaking work into tasks that can be delegated safely to coding agents.
• Running multiple human and agent-led workstreams concurrently.
• Providing agents with clear context, constraints, and acceptance criteria.
• Reviewing generated code for correctness, security, maintainability, and architectural fit.
• Using automation to accelerate testing, documentation, refactoring, and operational workflows.
• Measuring whether AI tooling produces genuine delivery improvements.
We do not expect blind reliance on generated output. The Engineering Lead remains accountable for the quality and
correctness of everything shipped by the team.
Success in the First 90 Days
• Understand the existing architecture, infrastructure, team capabilities, and delivery bottlenecks.
• Take ownership of backend and DevOps execution.
• Introduce a consistent planning, tracking, review, and release cadence.
• Establish visibility into ownership, progress, dependencies, and delivery risks.
• Improve CI/CD, testing, monitoring, and production-readiness practices.
• Create an effective delegation model across engineers and AI agents.
• Deliver at least one meaningful product or platform milestone predictably from planning through production.
Nice to Have
• Experience scaling an early-stage or growing engineering team.
• Experience hiring, mentoring, and performance-managing engineers.
• Experience with infrastructure as code, security practices, and cloud-cost optimisation.
• Experience managing migrations, reliability improvements, or legacy-system modernisation.
• Previous experience introducing AI-assisted development workflows into an engineering team.
Who Will Succeed in This Role
You are likely to succeed if you are equally comfortable discussing architecture, reviewing code, resolving a production incident, planning a release, and having an accountability conversation with an engineer. You bring structure without creating unnecessary bureaucracy and know how to turn product priorities into consistent, high-quality delivery.
Join our product development team at Planview as a Senior Software Engineer I and become a pivotal force on the Viz Core Team. This role offers the unique opportunity to shape and lead the development of data-processing pipelines and APIs that are at the heart of our software solutions. These solutions are designed to streamline and enhance the efficiency of software delivery, resonating deeply with software engineers who strive to build better and faster.
At Planview Viz, which is powered by the innovative “Flow Framework,” you will tackle complex data challenges and develop scalable solutions within an AWS cloud environment. Your efforts will be crucial in revolutionizing how businesses harness and interpret vast amounts of workflow data, transforming it into actionable insights that propel organizational efficiency and effectiveness.
Responsibilities (What you'll do)
- Create and refine powerful data-processing architectures that integrate seamlessly with a diverse array of external tools, enhancing the way software is delivered across industries.
- Drive operational excellence by critically analyzing problems, defining requirements, and devising robust solutions that push the boundaries of technology.
- Lead and inspire a team of talented engineers, promoting a culture of ownership, meticulous attention to quality, and proactive problem-solving.
- Stay at the cutting edge of technology by updating and expanding your team’s knowledge of cloud architectures, data processing, and advanced analytics, ensuring that you and your team remain leaders in technological innovation.
- Make a direct impact on the efficiency and effectiveness of software delivery worldwide through innovation and leadership.
Qualifications (What you'll bring)
Who We’re Looking For
The ideal candidate is a seasoned professional in cloud software development with a strong foundation in data processing and scalable software systems. You thrive in collaborative environments and are passionate about advancing cloud technology and data architecture to new heights. You are a leader who enjoys mentoring, guiding, and inspiring others.
Preferred Qualifications
Skills, Knowledge, and Expertise
- A degree in Computer Science, Engineering, or a related field.
- 6+ years of experience with a modern programming language, with a focus on back-end systems and cloud-based technologies.
- Strong capability in architecting and designing robust, scalable software systems.
- Proficiency in AWS or another popular cloud platform.
Additional Qualifications
- Experience with big-data technologies such as Spark and Apache Kafka.
- Experience with Java (version 17), Scala, or other JVM programming languages.
- Experience with tools such as Amazon Redshift and MongoDB.
- Experience with continuous integration and continuous deployment tools such as GitHub, Jenkins, Travis CI, or similar platforms.
- Proficiency in test-driven development.
- Experience with containers and orchestration tools such as Kubernetes.
- Experience working on remote or distributed teams and projects.
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










