Senior Backend Developer
Ken Research Pvt. Ltd.
Job Description
Job Title: Senior Backend Developer – Lead Engineer
Location: Gurgaon (WFO, 5 Days)
Department: Technology / Product Engineering
Reporting To: CMO / CDO
Employment Type: Full-Time, Permanent
Experience: 3+ Years
Company Profile
Ken Research is a global strategy consulting and market intelligence firm supporting enterprises, financial institutions, investors, and government bodies across India, Southeast Asia, the Middle East, and global markets.
Our engineering and digital transformation teams build scalable platforms that power:
- AI-enabled tools for insight generation
- Customer portals & internal delivery productivity solutions
We focus on engineering excellence, speed, automation, and system reliability.
Role Summary
We are hiring a Senior Backend Developer (Lead Engineer) to architect, develop, and optimize backend systems that support Ken Research’s next-generation consulting, research, and AI-driven platforms.
You will own backend development end-to-end, work extensively with Python, Django, DRF, Gunicorn, manage scalable deployments, and integrate search, automation, and LLM-backed workflows where needed.
The role requires a startup mindset, strong accountability, system design clarity, and the ability to collaborate directly with the CMO/CDO on product vision, architecture, and technical decisions.
Key Responsibilities
- Architect, build, and optimize backend systems using Python, Django, DRF
- Develop scalable microservices and REST APIs with secure, modular design
- Build background workers for asynchronous tasks (Celery/RQ/SQS)
- Maintain clean, testable, high-performance backend code
2. Database, Search & Performance Optimization
- Design & optimize relational databases (PostgreSQL/MySQL)
- Implement caching (Redis), indexing, and query optimization
- Integrate and maintain Elasticsearch for scalable search
- Improve system performance, concurrency handling, and reliability
3. API Engineering & Integrations
- Build secure APIs for internal and external integrations
- Implement authentication, RBAC, rate-limiting, throttling
- Integrate AI/LLM services for automation and insight workflows (preferred)
- Build backend layers for portals, dashboards, workflows, and internal tools
4. CI/CD, DevOps & System Reliability
- Set up and manage CI/CD pipelines (GitHub Actions / Jenkins / GitLab)
- Ensure automated deployments, rollback mechanisms, and environment stability
- Implement logging, monitoring, and error tracking (Sentry/ELK Stack)
- Support scalable infrastructure and uptime improvements
- Work directly with CMO/CDO on product vision, system architecture, and release planning
- Collaborate with product, frontend, DevOps, analytics, and LLM teams
- Mentor junior backend developers and build internal engineering capability
- Operate with complete ownership from planning → development → deployment
Preferred Technical Exposure (Value-Add)
Not mandatory but strongly preferred
- Elasticsearch advanced features (analyzers, scoring, boosting)
- LLM/AI integrations: OpenAI, Gemini, Claude
- Embeddings, vector databases (Pinecone, Weaviate, Chroma)
- Event-driven systems, automation, workflow orchestration
Qualifications & Skills Required
Education
- Bachelor’s/Master’s degree in Computer Science, Engineering, or related technical field
Experience
- 3+ years hands‑on backend engineering
- Deep experience with Python, Django, DRF
- Experience with CI/CD, Elasticsearch, Docker, Linux, Redis
Technical Skills
- Django, DRF, Python
- Elasticsearch
- Redis, Celery/RQ
- System debugging & performance optimization
Soft Skills & Mindset
- High accountability and ownership
- Startup mindset: speed, autonomy, clarity
- Strong communication and cross‑team collaboration
- Ability to break down complex problems into actionable development tasks
- Attention to detail and execution discipline
- API uptime, stability, and response‑time improvements
- Reduction in production issues & bug counts
- Measurable improvements in backend performance
Delivery KPIs
- On‑time delivery of backend modules
- Zero‑regression CI/CD releases
- Successful integration of Elasticsearch & LLM workflows
System KPIs
- Scalability enhancements
- Infrastructure reliability & monitoring improvements