About Innefu Labs

Innefu Labs is an AI-driven information security and data analytics company (founded 2010) that builds solutions across cybersecurity, facial biometrics, predictive intelligence and national/cyber security domains. The company works with government and enterprise customers and positions itself as a research-driven security & analytics vendor. :contentReference[oaicite:1]{index=1}

Recent public financial/market snapshots place Innefu’s FY2023–24 revenue in the neighborhood of INR ~64 crore and show Series-A funding history and growth indicators cited by multiple business-data sources. (Note: these are third-party company estimates/records — check official filings for audited numbers.) :contentReference[oaicite:2]{index=2}

Role summary

As a Senior Python Developer you’ll own design, development and maintenance of backend Python applications, collaborate with cross-functional teams, mentor juniors, and work on components like ETL frameworks and Elasticsearch. Familiarity with Django/Flask is a plus; strong Core Python and software design-patterns experience is expected. Immediate joiners are preferred. :contentReference[oaicite:3]{index=3}

• Key responsibilities: lead backend design, implement robust Python services, performance optimisation, code reviews, mentor junior devs, work with Elasticsearch & ETL pipelines. :contentReference[oaicite:4]{index=4}
• Qualifications: Bachelor’s in CS/Engineering (or equivalent), 2–5+ years Python experience, strong problem solving, good communication. :contentReference[oaicite:5]{index=5}

Salary & compensation

Salary disclosed: Not specified on the job posting. If you need a working benchmark for a Senior Python role (2–5 yrs) in Delhi/Delhi NCR, typical market ranges (estimates) are:

• Base (approx.): ₹6 LPA – ₹18 LPA depending on exact seniority, domain (cybersecurity/AI) and company stage.
• Senior/Lead hires with domain expertise (security/AI) can command the higher end or additional performance/ESOP components.

These are estimates — the job posting does not disclose pay. Confirm exact compensation during the interview/offer stage. Sources used for company size/financial context are cited above. :contentReference[oaicite:6]{index=6}

How to prepare (practical checklist)

1. Core Python: strong grasp of data structures, OOP, concurrency (asyncio, threading), memory/profile analysis and idiomatic patterns.
2. Web frameworks: hands-on with Django and/or Flask — writing APIs, middleware, authentication, and testing (pytest / Django TestCase).
3. APIs & integration: design RESTful APIs, versioning, OpenAPI/Swagger, API security best practices (JWT, OAuth basics).
4. Datastores & search: SQL (Postgres/MySQL), NoSQL (Redis, Mongo) and Elasticsearch basics (indexing, mapping, query DSL) — the role mentions ES experience. :contentReference[oaicite:7]{index=7}
5. ETL & data pipelines: experience building/maintaining ETL frameworks, data ingestion, transformation, monitoring and tuning.
6. DevOps & deployment: Docker, CI/CD pipelines, familiarity with AWS/GCP and deployment patterns (blue/green, canary); container orchestration basics (Kubernetes is useful).
7. Testing & code quality: unit+integration testing, linting, type hints (mypy/pyright), code reviews and design patterns.
8. System design: prepare to discuss scalable architecture for backend services, caching strategies, async processing and trade-offs.
9. Security mindset: since Innefu focuses on security, review OWASP Top 10, secure coding patterns, and authentication/authorization flows.
10. Mock interviews & projects: practice coding problems (medium-hard), system-design mock interviews and prepare 1–2 small projects demonstrating ETL/Search integrations or secure API design.

Common / likely interview questions

• Explain GIL and how you’d handle CPU-bound vs IO-bound workloads in Python.
• Design an ETL pipeline for ingesting, normalizing and indexing logs into Elasticsearch — discuss schema, scaling and failure handling.
• How would you design a rate-limited REST API for an authentication microservice?
• Explain a situation where you used design patterns to solve a maintainability problem — include code/design trade-offs.
• Debugging/performance: how to profile a slow Python service and fix a memory leak.
• Codes/mini-challenges: implement a threaded/async producer-consumer, or write a small Flask/Django endpoint with validation and unit tests.

Company culture & employee feedback

Public employee reviews show broadly positive ratings on Glassdoor (around ~4.2–4.3/5) highlighting supportive management, learning opportunities and positive work culture — with the New Delhi office frequently mentioned. At the same time, some review sites note mixed feedback on pay and occasional workload concerns. As with any employer, reviews vary by team and timeframe; treat these as directional signals and confirm details during interviews.

• Pros (from employee reviews): good learning culture, supportive management, interesting security/AI projects, on-time salary (reported by several reviewers).
• Cons (from employee reviews): some reports of salary satisfaction below expectations on aggregator sites and occasional weekend/availability needs depending on project. Confirm with recruiter.

Latest trends / company direction

Innefu has been positioning itself at the intersection of AI and national/cyber security — investing in analytics, biometric authentication and predictive intelligence. Public filings and company materials indicate growth in enterprise/government contracts and investments in product R&D and deployment at scale. Expect the product/engineering teams to focus on secure, scalable AI-data pipelines and integrations with government/enterprise systems.

Financial snapshot & credibility

Third-party databases list Innefu’s FY2023–24 revenue around INR ~64 crore and note Series A funding in prior years; company records show active operations and formal filings (RoC). These are third-party summaries — for audited financials consult official filings or the company’s investor relations.

Pros & Cons — Quick summary for applicants

How to apply (next steps)

1) Click the Apply button at the top or use the original Hirist link.
2) Keep an updated resume that highlights: Python projects, Elasticsearch/ETL experience, APIs & deployments, and any security/biometrics work.
3) Prepare a short bullet list (1–2 lines) of measurable outcomes for any past projects (latency reduced, volume ingested, detection accuracy improved, etc.).
4) If selected, ask the recruiter about compensation band, notice period flex, and remote/hybrid policy before final rounds.

Apply on Hirist — Innefu Labs Senior Python Software Engineer