Role Summary

You will design, build, and operate backend systems that must scale, remain reliable under load, and evolve over time without collapsing under complexity.

This is not a feature factory role. You will own systems end-to-end, make architectural decisions under real constraints, and be accountable for how your code behaves in production.

If your experience is limited to building APIs without owning system behavior in production, this is not the role for you.

Responsibilities

• Design and operate backend systems handling real production traffic, with clear understanding of bottlenecks, trade-offs, and failure modes

• Own services end-to-end, including design, implementation, deployment, monitoring, and production stability

• Debug and resolve production issues under pressure, including identifying root causes and implementing long-term fixes

• Make architectural decisions balancing performance, cost, simplicity, and scalability

• Continuously improve system reliability, latency, and efficiency

• Define and enforce engineering standards through code reviews and design feedback

• Mentor engineers by raising the bar, not by being polite

• Push back on unclear or weak product and technical decisions when needed

• Use AI tools to accelerate development and reasoning, without outsourcing critical thinking

Requirements (Non-Negotiable)

System Design & Scale

• Have designed and operated backend systems handling meaningful production scale (high request volume, large datasets, or multi-tenant systems)

• Can clearly explain:

  • System architecture you designed

  • Bottlenecks you encountered

  • Trade-offs you made (latency, consistency, cost, complexity)

• Experience evolving systems over time, not just building greenfield projects

Distributed Systems & Data

• Hands-on experience dealing with data consistency, concurrency, and failure scenarios in production

• Understand practical implications of:

  • Eventual consistency

  • Idempotency

  • Retries and failure handling

• Experience using queues, background processing, and asynchronous workflows in real systems

• Can explain where distributed systems add value and where they introduce unnecessary complexity

Production Ownership

• Have been directly responsible for production incidents, including:

  • Debugging under pressure

  • Mitigation and recovery

  • Root cause analysis

• Comfortable being accountable for uptime, performance, and system health

• Experience using logs, metrics, and tracing to diagnose issues

• Understand how systems fail, not just how they work

Performance & Efficiency

• Experience identifying and fixing performance bottlenecks (CPU, memory, I/O, database, network)

• Have improved systems in measurable ways (latency reduction, cost optimization, throughput increase)

• Understand trade-offs between performance, cost, and complexity

Ownership & Decision-Making

• Owns systems, not just tasks

• Makes decisions under constraints and accepts responsibility for outcomes

• Can justify technical choices clearly, including what was not chosen and why

• Can move forward without perfect requirements

Engineering Quality & Leadership

• Sets and enforces code quality standards through reviews

• Writes code that is maintainable, testable, and production-ready

• Identifies weak designs and pushes for better alternatives

• Raises the capability of the team

Architecture Judgment

• Experience working with microservices, monoliths, or hybrid systems

• Knows when to avoid unnecessary complexity

• Has simplified or refactored over-engineered systems

• Understands long-term cost of architectural decisions

AI-Assisted Development (Required)

• Actively uses tools such as Claude, Cursor, GitHub Copilot, or similar in daily work

• Uses AI for:

  • Faster iteration and prototyping

  • Debugging and exploring edge cases

  • Evaluating implementation or architecture options

• Can demonstrate specific examples where AI improved development speed or decision-making

• Critically evaluates AI-generated output:

  • Identifies incorrect assumptions

  • Verifies correctness before using in production

• Does not rely on AI for fundamental reasoning or system design

Baseline

• Strong fundamentals in data structures, algorithms, and software design

• Typically 7+ years of backend experience, but depth matters more than years

Nice-to-Have (Strong Signals)

• Experience operating systems at high scale (large traffic, large datasets, or strict SLAs)

• Experience with cloud infrastructure (AWS, GCP, Azure)

• Experience with containerized environments and orchestration (Docker, Kubernetes)

• Experience migrating systems (monolith to distributed, or simplifying distributed systems)

• Experience reducing infrastructure cost or significantly improving performance

• Experience working in fast-moving product environments

What We Don’t Want

• Engineers who have only built CRUD APIs without owning system behavior in production

• Engineers who cannot debug production issues independently

• Engineers who rely on tools, frameworks, or AI without understanding underlying systems

What Success Looks Like

• You design systems that scale without constant firefighting

• You improve performance, reliability, or cost in measurable ways

• You make decisions that simplify systems over time, not complicate them

• Other engineers become stronger because you are on the team
  

What We Offer

Work That Actually Matters

• You will work on real systems used in production by international clients, not internal tools or low-impact features

• You will face real engineering problems, scaling, performance, reliability, not just API wiring

• Your decisions will have visible impact, both when things go right and when they fail

Engineering Culture

• Developer-first environment where technical decisions are respected and driven by reasoning, not hierarchy

• High ownership culture, you are trusted to make decisions and expected to take responsibility for outcomes

• You will work with engineers who care about system design, code quality, and long-term maintainability

• Growth comes from solving hard problems, not attending training sessions

Growth & Career Progression

• Clear, merit-based growth, strong engineers move faster based on impact, not tenure

• Opportunity to influence architecture and technical direction, not just implement tasks

• Continuous exposure to complex systems that push your technical limits

Compensation & Benefits

• The salary range starts from 1,50,000৳ depending on skills and experience.

• Performance-based yearly salary increments

• Two Eid bonuses annually

Leave & Flexibility

• Five-day work week, weekends off (Saturday and Sunday)

• Flexible working hours

• 20 days of paid annual leave

• Public holidays as per government policy

• Leave encashment options

Family & Wellbeing

• Six months of maternity leave

• Two weeks of paternity leave

• Childbirth bonus

• Marriage bonus

• Ramadan Cost Adjustment.

• Supplemental Security Income - QAQI (Quarterly salary Adjustment and Quarterly salary Increment) and based on dependent family members

• Hospitalization coverage for:

  • Self

  • Spouse

  • Children

  • Parents (including spouse’s parents)

Work Environment

• Fully subsidized lunch, snacks, and beverages

• Regular team events and company gatherings, including cross-border & international gatherings!

• Collaborative environment focused on engineering excellence

Global Exposure

• Work with international clients and distributed teams

• Opportunities for short-term or long-term work abroad

What This Is Not

• Not a place where you hide behind tickets

• Not a place where someone else owns production issues

• Not a place where average performance is acceptable