L #2504
Applications open
Full-Time Job
Python Backend Engineer
Scry AI
About the role
Company: SCRY AI
Location: Multiple
Experience: 3+ year
Employment Type: Full-time
About Us
SCRY AI is an innovative AI-driven technology company focused on building intelligent, scalable, and high-performance solutions. We work with modern technologies across Software Engineering, AI/ML, and Data to solve real-world business problems and deliver impactful digital products.
Role Overview
We are looking for a skilled Software Engineer – Python Backend with strong experience in building scalable APIs, backend services, and database-driven applications. The ideal candidate should be hands-on with Python, asynchronous programming, SQL, and API development, and comfortable working closely with UI/Frontend teams to deliver reliable end-to-end solutions.
Key Responsibilities
- Design, develop, and maintain scalable, high-performance backend applications using Python.
- Build robust REST APIs and backend services using frameworks such as FastAPI or Flask.
- Develop asynchronous and concurrent applications using asyncio, background workers, queues, and multiprocessing where required.
- Design and optimize database schemas, SQL queries, joins, indexes, stored procedures, and transactions.
- Work extensively with PostgreSQL/MySQL and other relational databases.
- Collaborate with UI/Frontend teams on API contracts, request/response structures, authentication, error handling, and integration.
- Build APIs capable of handling high traffic, concurrent requests, and real-time workloads.
- Optimize API and database performance by identifying slow queries, bottlenecks, inefficient calls, and resource utilization issues.
- Integrate backend services with third-party APIs, external systems, and enterprise applications.
- Implement authentication, authorization, validation, logging, exception handling, and API security.
- Write clean, reusable, maintainable, and well-documented code; develop unit/integration tests and participate in code reviews.
- Containerize applications using Docker and support deployment, troubleshooting, monitoring, scalability, and reliability across environments.
Key Qualifications
- 3+ years of software engineering experience with strong hands-on experience in Python.
- Strong experience with FastAPI/Flask, REST APIs, asynchronous programming, asyncio, concurrency, background jobs, and message queues.
- Excellent knowledge of SQL and relational databases, particularly PostgreSQL/MySQL, including complex queries, CTEs, joins, aggregations, indexes, and transactions.
- Experience with database schema design, data modeling, query optimization, connection pooling, and performance tuning.
- Understanding of API scalability, caching, high-concurrency systems, and backend performance optimization.
- Experience integrating backend APIs with Frontend/UI applications and third-party systems.
- Good understanding of Git, Docker, Linux, testing, debugging, and CI/CD.
- Experience with Redis, Kafka/RabbitMQ, or similar caching and messaging technologies is a plus.
- Experience with AWS or other cloud platforms is preferred.
- Strong problem-solving, communication, collaboration, and ownership skills, with the ability to work independently in a fast-paced environment.
Good to Have
- Experience with Kubernetes, microservices, cloud-native architectures, and production observability.
- Exposure to event-driven architectures, distributed systems, API gateways, and performance/load testing.
- Experience working with AI/ML or GenAI backend integrations and deploying Python-based AI services is a plus.
If this role interests you, follow our page to stay updated on more job opportunities and insights into how AI companies build scalable backend systems, develop reliable APIs, and support high-performance enterprise applications and intelligent technology platforms.
Eligibility & process
Who can apply
Seniority: Entry level. Employment type: Full-time
Skills & stack
Selection process
Details are shared by the recruiter after shortlisting.
Prep kit
20 resourcesStudy material 4
Aptitude Practice Questions & Mock Tests
Curated logical, quantitative, and verbal reasoning problems for the initial online screening round.
Company-Specific Interview Preparation Corner
Detailed interview experiences, exam formats, and previous test questions for Scry AI and tech roles.
Technical Placement Question Bank
High-yield coding cheat sheets, core CS fundamentals (OOP, DBMS, OS, Networks), and rapid revision guides.
Algorithm, DSA & Live Code Debugger Practice
Hands-on problem sets to improve coding speed and step-by-step memory debugging.
Company-specific guides 4
APTITUDE & LOGIC
Aptitude Practice Questions & Online Mock Tests
Curated logical, quantitative, and verbal reasoning problems to sharpen reasoning skills required for the initial screening test.
COMPANY GUIDE
Scry AI Interview Preparation Corner
Comprehensive guide covering typical interview formats, common questions, and preparation tips for Scry AI and off-campus tech roles.
MOCK TESTS & PAPERS
Comprehensive Interview Prep Resources & Syllabus
Collection of previous year questions, company-specific test patterns, and interview experiences for technical and HR rounds.
CODING PRACTICE
Algorithm and Data Structure Problem Set
Practice problems to improve coding proficiency and algorithm problem-solving speed for technical rounds.
Likely coding questions 4
Round-wise strategy 4
Round 1: Online Assessment (OA)
Aptitude, Quantitative Logic & 2 Coding Problems
Focus on accuracy and speed. Practice arrays, strings, and standard arithmetic puzzles.
Round 2: Technical Interview 1
Core Tech Stack (Python, SQL, FastAPI, Flask, REST APIs, Microservices, PostgreSQL, MySQL) & Live Code Tracing
Explain your thought process aloud. Analyze time & space complexities before coding.
Round 3: System Design & Problem Solving
Database Schemas, APIs & Architecture Basics
Clarify edge cases, diagram schemas cleanly, and discuss scalability trade-offs.
Round 4: HR & Cultural Fit Discussion
Scry AI Core Values, Learning Agility & Offer Terms
Demonstrate passion, strong communication, and readiness for full-time collaboration.
Technical questions 5
What is the difference between WHERE and HAVING clauses in SQL? Answer
Model answer: WHERE filters rows before any groupings are applied, while HAVING filters aggregated groups after GROUP BY has executed.
Explain SQL Window functions: ROW_NUMBER(), RANK(), and DENSE_RANK(). Answer
Model answer: ROW_NUMBER() assigns unique sequential integers. RANK() assigns identical ranks to ties and skips ranks. DENSE_RANK() assigns identical ranks to ties without skipping rank numbers.
How do you handle NULL and missing values during data cleaning in Python/Pandas? Answer
Model answer: Use .isna().sum() to identify missing values. Impute with mean/median using .fillna() or remove with .dropna(subset=[...]) depending on variance impact.
What is the difference between Star Schema and Snowflake Schema in Data Warehousing? Answer
Model answer: Star Schema has denormalized dimension tables directly connected to the central Fact table. Snowflake Schema normalizes dimension tables into sub-dimensions to minimize redundancy.
How do you calculate MoM (Month-over-Month) growth in SQL? Answer
Model answer: Use LAG(revenue, 1) OVER (ORDER BY month) to fetch the previous month's revenue and compute (revenue - prev_revenue) / prev_revenue * 100.
Behavioural & HR questions 3
Why do you want to join Scry AI as a Python Backend Engineer?
Highlight Scry AI's market reputation, recent tech innovations, and how your skills in Python directly solve their team's objectives.
Highlight Scry AI's market reputation, recent tech innovations, and how your skills in Python directly solve their team's objectives.
Describe a challenging bug or academic project roadblock and how you resolved it.
Use the STAR method: Situation (project context), Task (what needed solving), Action (specific tools/logic applied), Result (quantifiable positive outcome).
Use the STAR method: Situation (project context), Task (what needed solving), Action (specific tools/logic applied), Result (quantifiable positive outcome).
How do you handle strict deadlines or sudden scope changes?
Explain your prioritization strategy, proactive communication with mentors/peers, and agile mindset.
Explain your prioritization strategy, proactive communication with mentors/peers, and agile mindset.
Competitive Package
Mumbai, India
Seniority: Entry level. Employment type: …
