Sr Backend Engineer (Tech Lead )

Senior Software Engineer – Backend

Company: House of EdTech (Goenka Kachave LLP)

Location: Bangalore, Hybrid

Job Type: Full-Time

Experience: 5+ Years

About the Role

House of EdTech is looking for a Senior Software Engineer – Backend to design, develop, and scale high-performance backend services and APIs supporting products used by millions of learners.

You’ll work closely with Product, Frontend, Data, and Engineering teams while taking end-to-end ownership of backend features and contributing to system architecture and technical decisions.

What You'll Do

• Design and develop scalable backend services and REST APIs.
• Build reliable systems capable of handling high traffic and large data volumes.
• Own backend features from design and development through deployment and monitoring.
• Work with microservices, databases, and distributed systems.
• Identify and solve performance, scalability, reliability, and security challenges.
• Participate in system design and architecture discussions.
• Conduct code reviews and contribute to engineering best practices.
• Mentor junior and mid-level engineers.
• Monitor production systems and troubleshoot incidents.

What We're Looking For

• 5+ years of professional backend development experience.
• Strong hands-on experience with Java, Python, Scala, C++, or a similar language.
• Experience building and operating large-scale distributed systems.
• Strong understanding of REST APIs, microservices, and databases.
• Experience with cloud/infrastructure technologies such as GCP, Docker, or Kubernetes.
• Strong software engineering fundamentals, including security, reliability, testing, and code quality.
• Experience with system design, architecture, and technical decision-making.
• Strong communication and cross-functional collaboration skills.
• Experience mentoring engineers is a plus.

Why Join House of EdTech?

• Work on products impacting millions of learners.
• Solve challenging backend and scalability problems.
• Take significant ownership of architecture and engineering decisions.
• Opportunity to grow into technical leadership and architectural ownership.
• Work in a fast-growing technology environment.

About the role

We are hiring a Principal Engineer to own the hardest technical problems in our product and see them through from first sketch to stable production. You will set technical direction, design systems that scale, and raise the engineering bar through your own work and the people around you. This is a hands-on leadership role: you write code, review designs, and ship.

What will you do?

You will own outcomes, not just tasks. Expect to spend your time on the following.

• Own projects end to end. Take an ambiguous problem, shape the requirements, design the solution, break down the work, deliver it to production, and stay accountable for how it runs afterwards.

• Lead system design. Author and review architecture for services, data pipelines and integrations, with clear trade-offs on scale, latency, cost, consistency and reliability.

• Write and review critical code. Build the hardest components yourself, and set standards for code quality, testing and maintainability through code and design reviews.

• Own deployment and operations. Design CI/CD, infrastructure and release strategies. Drive observability, on-call readiness, incident response and post-incident learning.

• Solve hard problems. Debug production issues across the stack, and find root causes in performance, concurrency, data and scaling problems.

• Mentor and multiply. Coach senior and junior engineers, grow future tech leads, and make the whole team faster and more confident.

• Partner across functions. Work with product, design, data and business teams to turn goals into technical plans, and to say no or reshape scope when needed.

• Shape technical strategy. Guide build-versus-buy decisions, manage tech debt, evaluate new technologies, and contribute to the engineering roadmap.

• Raise the bar. Help define engineering practices, hiring standards and culture, and take part in interviewing.

What are we looking for?

• Bachelor's degree in Computer Science or a related field, or equivalent practical experience.

Core engineering

• 10+ years of professional software engineering, with a track record of shipping and running production systems.

• Strong computer science fundamentals: data structures, algorithms and complexity, operating systems, networking, databases and concurrency.

• Fluency in at least one major backend language (for example Python, Go, Java, or Node.js/ TypeScript) and the ability to pick up others quickly.

• Deep knowledge of relational and NoSQL data stores: schema design, indexing, transactions, query tuning and replication.

System design and problem solving

• Proven ability to design distributed systems that are scalable, fault tolerant and cost aware, and to explain the trade-offs clearly.

• Experience with APIs, event-driven and asynchronous architectures, queues, caching and service-to-service communication.

• A structured approach to ambiguous problems: break them down, test assumptions, decide with incomplete data, and measure results.

• Strong debugging instincts, including performance profiling and production troubleshooting.

Delivery and operations

• Have led at least two significant projects from inception to production, including planning, milestones, risk management and launch.

• Hands-on experience with deployment: CI/CD pipelines, containers (Docker, Kubernetes), a major cloud (AWS, GCP or Azure), and infrastructure as code.

• Practical experience with monitoring, logging, alerting, SLOs and incident management.

• Habit of writing tests and automation, and of leaving systems more reliable than you found them.

Leadership and communication

• Experience leading engineers without formal authority, through influence, mentoring and clear technical writing.

• Excellent written and verbal communication: design docs, RFCs and concise updates to non-technical stakeholders.

• Ownership mindset, sound judgment on priorities, and comfort working in a fast-moving environment.

Nice to have

• Experience in fintech, lending or another regulated, data-heavy domain.

• Exposure to AI/ML or LLM-based systems in production: model serving, evaluation, retrieval, and cost and latency management.

• Deep experience with data engineering: streaming, batch pipelines, warehouses or search systems.

• Security and compliance awareness: authentication, encryption, audit trails, secure SDLC.

• Experience with multi-tenant SaaS, high-throughput systems or zero downtime migrations.

• Open-source contributions, conference talks, or technical writing.

• Experience scaling an engineering team or helping set up hiring and onboarding practices.

Why this role exists 

Most systems work at a low scale. 

Very few survive real production load, complex workflows, and enterprise edge cases. 

We are building a platform that must: 

1. Scale from 500K → 20M+ interactions/month 
2. Handle complex insurance workflows reliably 
3. Become easier to deploy as it grows, not harder 
4.  
5. This role exists to build the backend foundation that makes this possible. 

What you’ll do 

You will not just write services. 

You will design and own core platform systems. 

1. Scale the platform without breaking architecture 

1. Scale from 50K → 4M+ interactions/month 
2. Ensure: 
3. High availability 
4. Low latency 
5. Fault tolerance 
6. Avoid large rewrites — build systems that evolve cleanly 

2. Build the workflow automation (WA) engine 

1. Design a flexible system with: 
2. States 
3. Stages 
4. Cohorts 
5. Dynamic workflows 
6. Ensure workflows: 
7. Handle edge cases reliably 
8. Can be configured easily 
9. Move from: 
10. Hardcoded flows → configurable execution engine 

3. Build the insurance-specific data layer 

1. Design data models for: 
2. Policy states 
3. Claim workflows 
4. Consent tracking 
5. Ensure the system works across: 
6. Multiple insurers 
7. Multiple use cases 
8. Build a platform-first data layer, not use-case-specific hacks 

4. Make deployment and setup simple 

1. Ensure workflows and data models are: 
2. Easy to configure 
3. Easy to launch 
4. Reduce friction for: 
5. Product teams 
6. Deployment teams 

5. Create a compounding data advantage 

1. Build a data layer that: 
2. Improves with every deployment 
3. Captures structured signals 
4. Ensure data becomes a long-term edge, not just storage 

6. Own production reliability 

1. Participate in on-call rotation across 3 engineers 
2. Ensure: 
3. Incidents are handled quickly 
4. Root causes are fixed permanently 
5. Build systems where reliability is shared, not individual 

What success looks like 

1. Platform scales to 2M+ interactions/month smoothly 
2. Workflow engine supports complex, dynamic use cases 
3. Data layer enables fast deployment across accounts 
4. Edge cases are handled without constant firefighting 
5. System becomes easier to use as it grows 
6. Production issues are rare and predictable 

Who you are 

1. You have built: 
2. Scalable systems 
3. Distributed services 
4. You think in: 
5. Systems 
6. Data models 
7. Trade-offs 
8. You are comfortable owning: 
9. Architecture 
10. Production systems 

What will make you stand out 

1. Experience building: 
2. Workflow engines 
3. State machines 
4. Data-heavy platforms 
5. Strong understanding of: 
6. System design 
7. Distributed systems 
8. Failure handling 
9. Experience working in: 
10. High-scale production environments 

Why join 

1. You will build the core backend of an AI platform 
2. Your work directly impacts: 
3. Scale 
4. Reliability 
5. Product capability 
6. You will design systems that move from: 
7. Use-case specific → platform-level infrastructure 

What this role is not 

1. Not just API development 
2. Not limited to feature-level work 
3. Not disconnected from production realities 

What this role is 

1. A system architect 
2. A builder of scalable platforms 
3. A driver of long-term technical advantage 

One question to self-evaluate 

Can you design backend systems that scale, handle edge cases, and become easier to use as they grow? 

ABOUT

The Persona Labs is building a new kind of social platform focused on something most social products do not explicitly optimize for: helping people become real friends.

We want to help people discover interesting people around them, find meaningful common ground, start low-pressure interactions, continue promising conversations, create shared experiences, and ultimately build real-life friendships.

DISCOVER → CURIOSITY → COMPATIBILITY → INTERACTION → UNDERSTAND → IRL EXPERIENCE → FRIENDSHIP

THE AI LAYER - COMPANION INTELLIGENCE

Alongside the platform, we are building a proactive personal AI companion that learns about the user and helps them navigate this journey through personalized recommendations, suggestions, reminders, conversations, and experiences. 

THE OPPORTUNITY

We are looking for a Founding ML Engineer to build the intelligence layer of the platform from the ground up. This is a 0→1 Applied AI / ML role where you will work directly with the founder and Product Engineer to turn ambiguous problems around users, relationships, recommendations and personal intelligence into working systems.

You will be expected to:

Understand the problem → identify the signals → design the intelligence system → prototype → evaluate → deploy → learn → improve.

WHAT YOU WILL BUILD & OWN

USER INTELLIGENCE

User representations, behavioural models, interests, preferences, contextual signals, and evolving understanding of the user. MEMORY Short- and long-term memory, episodic/preference/relationship memory, retrieval, relevance and updating.

RECOMMENDATION & MATCHING

People discovery, compatibility, activity/experience recommendations, and personalized ranking.

INTENT & INTEREST

Infer what the user is trying to do and learn what they care about from behaviour, not only declared interests.

RANKING

Decide what should appear first across potentially thousands of relevant people, activities or experiences.

CONTENT INTELLIGENCE

Classification, toxicity, spam, policy signals, quality, relevance, and semantic understanding.

RELATIONSHIP INTELLIGENCE

Reciprocity, interaction health, shared interests, progression, declining engagement and shared activity.

NEXT-BEST-ACTION

Determine the most useful action now: show a person, suggest a question, recommend an activity, reconnect, or do nothing.

TRUST / SAFETY INTELLIGENCE

Fake-account signals, spam, abuse, behavioural anomalies, risky interactions and moderation assistance.

COMPANION INTELLIGENCE

Use signals and outputs to help the companion decide what to say, suggest, recommend or not do. 

WHAT YOUR DAY-TO-DAY LOOKS LIKE

• Translate ambiguous product problems into ML/AI system designs.

• Build models and intelligence pipelines using behavioural, relational and contextual signals.

• Develop recommendation, matching and personalization systems.

• Design memory and retrieval systems that help the companion understand the user over time.

• Build and evaluate LLM-powered and agentic workflows.

• Decide when to use traditional ML, rules, retrieval, ranking or LLMs.

• Prototype quickly, test assumptions and iterate based on real user behaviour.

• Work closely with the founder and Product Engineer to turn intelligence into product experiences.

• Design APIs and production systems that bring ML/AI capabilities into the application.

• Build evaluation, monitoring and feedback loops so the intelligence improves over time.

WHO SHOULD APPLY

• Experience: 0–4 years’ experience, including exceptional fresh graduates. Strong 1–3 year engineers and experienced 3–4 year product builders are welcome.

• Strong foundations in ML, Python, statistics and software engineering.

• Evidence of Building: Experience with AI/ML projects, recommendation systems, LLM applications or personalization is highly valued.

• Strong evidence of building: Shipped projects, research, hackathons, internships, open source or startup work. 

WHAT WE LOOK FOR

MACHINE LEARNING DEPTH

Can you understand the modelling problem underneath the application?

RECOMMENDATION & PERSONALIZATION

Can you reason about relevance, ranking, cold start and behavioural signals?

AI ENGINEERING

Can you turn LLMs and agents into reliable product capabilities rather than simple API wrappers?

USER INTELLIGENCE

Can you design systems that gradually understand a person from sparse and changing signals?

SYSTEMS THINKING

Can you move from a model to a production system with APIs, data, latency, cost and monitoring?

EVALUATION MINDSET

Can you determine whether the intelligence actually helped the user?

PRODUCT JUDGMENT

Can you decide what the system should do when there is no predefined answer?

SPEED OF EXECUTION

Can you move from idea → prototype → evaluation → production quickly and responsibly?

BUILD WITH US

You will join at a stage where many of the answers do not exist yet. You will not simply implement a model someone else selected; you will help decide how the product learns to understand people.

CAREERS:

Apply with your resume, GitHub, portfolio or shipped work.

https://forms.gle/12YpUSBY2Sqs5xjp8

www.thepersonalabs.com

We’re seeking a highly skilled, execution-focused Senior Backend Engineer with a minimum of 5 years of experience to join our team. This role demands hands-on expertise in building and scaling distributed systems, strong proficiency in Java, and deep knowledge of cloud-native infrastructure. You will be expected to design robust backend services, optimize performance across storage and caching layers, and enable seamless integrations using modern messaging and CI/CD pipelines.

You’ll be working in a high-scale, high-impact environment where reliability, speed, and efficiency are paramount. If you enjoy solving complex engineering challenges and have a passion for distributed systems, this is the right role for you.

Responsibilities—

• Design, develop, and maintain distributed backend systems at scale.
• Write high-performance, production-grade code in Java.
• Architect and optimize storage systems, ensuring efficient query performance and scalable data models.
• Implement caching strategies to reduce latency and improve system throughput.
• Build and manage services leveraging AWS cloud infrastructure.
• Develop resilient messaging pipelines using Kafka (or equivalent) for real-time data processing.
• Define and streamline CI/CD pipelines, ensuring rapid and reliable deployment cycles.
• Collaborate with product managers, frontend engineers, and DevOps to deliver end-to-end solutions.
• Monitor system performance, identify bottlenecks, and apply proactive fixes.
• Drive best practices in software engineering, testing, and code reviews. 

Requirements—

• 5+ years of experience in backend engineering, with deep hands-on coding experience.
• Strong proficiency in Java and familiarity with modern frameworks.
• Proven track record in building scalable distributed systems.
• Hands-on expertise with AWS services (e.g., EC2, S3, Lambda, DynamoDB, RDS).
• Solid understanding of messaging systems like Kafka, RabbitMQ, or similar.
• Strong grasp of query performance optimization and storage system design.
• Experience with caching solutions (Redis, Memcached, etc.).
• Familiarity with CI/CD tools (Jenkins, GitHub Actions, GitLab CI, etc.).
• Excellent problem-solving skills and ability to thrive in fast-paced environments.
• Strong communication and collaboration skills, with a proactive mindset.

Benefits—

• Best in class salary: We hire only the best, and we pay accordingly.
• Proximity Talks: Meet other designers, engineers, and product geeks — and learn from experts in the field.
• Keep on learning with a world-class team: Work with the best in the field, challenge yourself constantly, and learn something new every day.

About us—

Proximity is the trusted technology, design, and consulting partner for some of the biggest Sports, Media, and Entertainment companies in the world. We’re headquartered in San Francisco and have offices in Palo Alto, Dubai, Mumbai, and Bangalore.

Since 2019, Proximity has built high-impact, scalable products used by millions of users every day. Today, we are a global team of engineers, designers, product managers, and experts solving complex problems and building cutting-edge technology at scale.

About VerbaFlo.ai

VerbaFlo.ai is a fast-growing AI SaaS startup revolutionizing how businesses leverage AI-powered solutions. As a part of our dynamic team, you’ll work alongside industry leaders and visionaries to drive innovation and execution across multiple functions.

Role Overview

We are looking for a Senior Backend Engineer to design and develop user-friendly, scalable, and high-performance web applications. This role requires deep expertise in backend technologies, attention to detail, and the ability to collaborate with cross-functional teams.

Responsibilities

• Design, develop, and maintain scalable backend systems, APIs, and data pipelines.
• Collaborate closely with frontend engineers, product managers, and AI teams to deliver cohesive features and seamless user experiences.
• Ensure the reliability, security, and performance of backend systems.
• Write clean, maintainable, and efficient code using modern backend practices.
• Implement automated testing, CI/CD workflows, and infrastructure as code (where applicable).
• Own the end-to-end lifecycle of backend features, from architecture to deployment.
• Monitor production systems and resolve performance and scalability issues.
• Contribute to architectural decisions and help evolve our engineering best practices.

Requirements

• 4–6 years of experience in backend development in startups, preferably in SaaS or AI-driven products.
• Proficiency in Node.js, Python, or Go
• Deep understanding of RESTful API design.
• Strong experience with databases: PostgreSQL, MongoDB, ElasticSearch.
• Exposure to message queues, job schedulers, or event-driven architectures (e.g., SQS, Celery, etc).
• Familiarity with cloud platforms like AWS, GCP, or Azure and containerization tools (Docker, Kubernetes).
• Experience with Git, CI/CD tools, and writing unit/integration tests.
• Strong problem-solving skills and a mindset geared toward performance and security.
• Excellent communication and collaboration abilities.

Why Join Us?

• Work directly with top leadership in a high-impact role.
• Be part of an innovative and fast-growing AI startup.
• Opportunity to take ownership of key projects and drive efficiency.
• A collaborative, ambitious, and fast-paced work environment.
• Perks & Benefits: gym membership benefit, workation policy, and company-sponsored lunch.

If you’re looking for an exciting role that combines strategy, execution, and leadership exposure, we’d love to hear from you!

Our Story

At The Alter Office, we build what comes next. We operate as an internal innovation lab, creating stealth products, new business bets, and high-leverage systems designed to unlock disproportionate value for us and our partner company ITW Consulting.

Our work is not centered around being a conventional service partner. Instead, we focus on building products and platforms that solve complex, strategic problems and create long-term advantage. Where needed, we have stepped in on critical opportunities beyond the usual scope, especially when speed, product thinking, and execution depth mattered most.

About the Role

We are building a holistic AdTech platform that delivers premium value to both advertisers and publishers, and the backend is where that entire ecosystem actually runs - the ad marketplace, campaign creation, ad-serving decisioning, analytics collection, attribution, and ROAS measurement.

Concretely, that means large-scale architecture: the ad-serving systems that make real-time decisioning calls at volume, the scalable data platforms that ingest and process billions of events a day, the analytics platforms that turn that data into attribution and ROAS numbers advertisers and publishers trust, and the autonomous AI agents we're building to automate campaign optimization and decisioning across the platform.

We are looking for someone who is eager to learn, enjoys solving technical problems, and wants to grow beyond simply implementing tasks. You'll have opportunities to understand how backend systems connect to the product and gradually take ownership of larger parts of the platform.

Key Responsibilities

• Build and maintain backend APIs and services for our ad marketplace, campaign management, and analytics platforms.
• Work with senior engineers to design and implement scalable backend solutions.
• Develop RESTful APIs and asynchronous backend workflows.
• Work with SQL databases such as MySQL and PostgreSQL and NoSQL technologies such as MongoDB and Redis.
• Implement data models, database queries, caching, and basic performance optimizations.
• Contribute to backend infrastructure supporting analytics, attribution, and AI-powered platform features.
• Collaborate with product, frontend, backend, and DevOps teams to deliver end-to-end features.
• Implement authentication, authorization, and basic security practices under the guidance of senior engineers.
• Write clean, maintainable, documented, and tested code.
• Use Git and participate in code reviews and team development practices.
• Learn and contribute to deploying backend services on cloud platforms such as AWS, GCP, or Azure.
• Work with Docker for containerizing backend services.
• Contribute to CI/CD pipelines and development workflows.
• Help monitor, debug, and troubleshoot backend services in development and production environments.
• Explore event-driven and distributed architectures using technologies such as message brokers, WebSockets, or GraphQL where appropriate.

Requirements

• 1–2 years of professional backend engineering experience, including relevant internship or project experience.
• Proficiency in at least one backend language, with the ability and willingness to adapt to other languages such as Node.js/JavaScript, Go, Python, and Java.
• Good understanding of RESTful API design and backend fundamentals.
• Good understanding of asynchronous programming and how backend services communicate.
• Familiarity with relational databases such as MySQL or PostgreSQL.
• Familiarity with at least one NoSQL database such as MongoDB or Redis is a plus.
• Good understanding of data modeling and writing SQL queries.
• Familiarity with Git and software development workflows.
• Good understanding of Docker and containerized applications.
• Exposure to cloud platforms such as AWS, GCP, or Azure is a plus.
• Understanding of basic backend security concepts such as authentication, authorization, and secure API practices.
• Strong problem-solving and debugging skills.
• Good communication and willingness to collaborate with other engineers and product teams.
• Strong learning mindset and willingness to work with unfamiliar technologies.
• Comfortable working in a fast-paced environment with evolving priorities.

5 steps, and we tell you where you stand at each one.

Online Assessment : Evaluate coding skills, backend fundamentals, SQL, problem-solving, and technical understanding.

Technical Interview 1 : Discuss previous projects, backend experience, APIs, databases, system design, and production experience.

Take-Home Assessment : A practical backend assignment to evaluate code quality, architecture, scalability, testing, and ability to build a production-ready solution.

Technical Interview 2 : Deep dive into the take-home assignment, system design, technical decisions, scalability, debugging, cloud, and architecture.

HR Interview : Discuss communication, ownership, culture fit, career goals, compensation, availability, and overall expectations.

Strong Backend Software Engineer Profile with strong Core Java expertise

2

Mandatory (Experience 1): Must have 2+ years of hands-on backend software engineering experience.

3

Mandatory (Experience 2): Must be able to design and implement moderately complex features with minimal supervision, and contribute to system design and architecture discussions.

4

Mandatory (Experience 3): Must be comfortable owning business-critical production components — maintaining connectors, handling customer escalations, security fixes, bug fixes, and building new features end-to-end.

5

Mandatory (Tech skill 1): Must have strong, current Core Java depth with solid, clear coding fundamentals — Java is the primary skill for this role. Deep hands-on core engineering strength matters more than framework knowledge.

6

Mandatory (Tech skill 2): Must have strong core backend engineering fundamentals and experience with scalable systems (connectors handle millions of events/data points daily across customers).

7

Mandatory (AI Fluency): Must have demonstrated, hands-on use of AI coding assistants (Claude, GitHub Copilot, Cursor, etc.) as a core part of the daily workflow — scaffolding, writing tests, reviewing code, and debugging — with the ability to write precise, effective prompts for production-quality output, decompose tasks so AI assistance is effective, and critically evaluate AI-generated code for correctness, security, and standards before merging.

8

Mandatory (Database): Hands-on database / JDBC integration experience in a production environment.

9

Mandatory (Company): Must come from a product company background (B2B SaaS or B2C both acceptable).

10

Mandatory (Note1): This is a 3-month contract role. Candidate must be comfortable with the contract engagement and able to join immediately (urgent — onboarding within ~a week)