Engineer

Candidates typically face a timed online coding test followed by a 30‑minute technical interview focusing on system design and AI pipeline implementation. The difficulty is moderate to high, with emphasis on problem‑solving speed and clear communication. Preparing with coding platforms and reviewing AI workflow case studies greatly improves performance.

Docs promotes a collaborative, merit‑based culture where engineers are given autonomy to experiment and ship features quickly. The company emphasizes work‑life balance with flexible remote policies and regular learning sessions, ensuring steady career growth.

B.Tech/B.E. or M.Tech in Computer Science, Information Technology, Electronics & Communication or related fields; CGPA 6.5/10 or above; batch years 2025, 2026 or 2027; no active backlogs; strong foundation in data structures, algorithms and system design; good communication skills.

Round 1: Online assessment (coding + aptitude) → Round 2: Technical interview (system design, coding, AI workflow discussion) → Round 3: HR interview (culture fit, expectations)

Docs is a fast‑growing AI startup focused on delivering end‑to‑end production‑grade artificial‑intelligence solutions for small and medium businesses (SMBs). The company’s portfolio spans critical sectors such as healthcare, recruitment, lending, renewable energy, and marketing. By building voice agents, multi‑agent pipelines, and agentic workflows, Docs helps its clients automate repetitive tasks, improve decision‑making, and scale operations without massive engineering overhead. The core team combines deep expertise in machine learning, cloud infrastructure, and product engineering, and has successfully shipped several SaaS products that are now used by hundreds of SMBs across India and Southeast Asia. The culture is built around rapid iteration, data‑driven product development, and a relentless focus on reliability and security. The role of Engineer at Docs is a hands‑on, full‑stack position where you will own the lifecycle of AI‑driven features from concept to production. You will write production‑grade code, design scalable pipelines, and collaborate closely with product managers, data scientists, and DevOps engineers. The hiring process includes a quick technical assessment followed by a short Loom video interview (approximately ten minutes) to gauge communication and problem‑solving skills. Key Responsibilities: 1. Design, develop, and maintain micro‑services that power voice agents and multi‑agent pipelines. 2. Implement end‑to‑end AI workflows, including data ingestion, model inference, and result orchestration. 3. Write clean, testable code in Python/Go and ensure high code coverage. 4. Optimize system performance and latency for real‑time applications. 5. Collaborate with data science teams to integrate new models into production. 6. Manage CI/CD pipelines using GitHub Actions or Jenkins. 7. Monitor production systems, set up alerts, and troubleshoot incidents. 8. Participate in code reviews and mentor junior engineers. 9. Contribute to architectural decisions and documentation. 10. Stay updated with the latest AI research and apply relevant techniques to improve product capabilities. Tech Stack: Python, Go, Docker, Kubernetes, AWS (SageMaker, Lambda), PostgreSQL, Redis, gRPC, REST APIs, Terraform, Prometheus/Grafana. Growth Path: Starting as an Engineer, you can progress to Senior Engineer, Lead Engineer, and eventually to Architecture or Product Management roles, with exposure to cutting‑edge AI technologies and leadership opportunities. Why Join Docs? You will work on real‑world AI products that impact thousands of businesses, gain deep expertise in both software engineering and machine learning, and enjoy a culture that rewards ownership, creativity, and continuous learning. The fast‑paced environment ensures you are constantly challenged and able to see the tangible results of your work.