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Python Developer
Python Developer
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Python Developer

Nilam Surti's profile picture
Posted by Nilam Surti
0 - 0 yrs
₹1.2L - ₹4L / yr
Bengaluru (Bangalore)
Skills
skill iconPython
skill iconMongoDB
FastAPI
Artificial Intelligence (AI)
skill iconGo Programming (Golang)

The requirements are as follows:


1) Familiar with the the Django REST API Framework.


2) Experience with the FAST API framework will be a plus


3) Strong grasp of basic python programming concepts ( We do ask a lot of questions on this on our interviews :) )


4) Experience with databases like MongoDB , Postgres , Elasticsearch , REDIS will be a plus


5) Experience with any ML library will be a plus.


6) Familiarity with using git , writing unit test cases for all code written and CI/CD concepts will be a plus as well.


7) Familiar with basic code patterns like MVC.


8) Grasp on basic data structures.


You can contact me on nine three one six one two zero one three two

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About appscrip

Founded :
2011
Type :
Products & Services
Size :
100-1000
Stage :
Profitable

About

Mobile app development services company based in USA & India. Accelerating startups & entrepreneurs with its pre-built mobile app products.
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Summary:

We are seeking a highly skilled Python Backend Developer with proven expertise in FastAPI to join our team as a full-time contractor for 12 months. The ideal candidate will have 5+ years of experience in backend development, a strong understanding of API design, and the ability to deliver scalable, secure solutions. Knowledge of front-end technologies is an added advantage. Immediate joiners are preferred. This role requires full-time commitment—please apply only if you are not engaged in other projects.

Job Type:

Full-Time Contractor (12 months)

Location:

Remote / On-site (Jaipur preferred, as per project needs)

Experience:

5+ years in backend development

Key Responsibilities:

  • Design, develop, and maintain robust backend services using Python and FastAPI.
  •  Implement and manage Prisma ORM for database operations.
  • Build scalable APIs and integrate with SQL databases and third-party services.
  • Deploy and manage backend services using Azure Function Apps and Microsoft Azure Cloud.
  • Collaborate with front-end developers and other team members to deliver high-quality web applications.
  • Ensure application performance, security, and reliability.
  • Participate in code reviews, testing, and deployment processes.

Required Skills:

  • Expertise in Python backend development with strong experience in FastAPI.
  • Solid understanding of RESTful API design and implementation.
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Added Advantage:

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Eligibility:

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Recruiting Bond
at Recruiting Bond
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Pavan Kumar
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Location: Mumbai, Maharashtra, India

Sector: Technology, Information & Media

Company Size: 500 - 1,000 Employees

Employment: Full-Time, Permanent

Experience: 10 - 14 Years (Engineering Leadership)

Level: Engineering Manager / Group EM


ABOUT THIS MANDATE :


Recruiting Bond has been exclusively retained by one of India's most prominent and well-established digital platform organisations operating at the intersection of Technology, Information, and Media to identify and place an exceptional Engineering Manager who can lead engineering teams through an enterprise-wide AI adoption and digital transformation agenda.


This is a high-impact, hands-on leadership role at the nexus of people, product, and technology. The organisation is executing one of the most ambitious AI transformation programmes in its sector and this Engineering Manager will be a core driver of that change. You will lead multiple squads, own engineering delivery end-to-end, embed AI tooling and practices into the team's DNA, and shape the engineering culture of tomorrow.


We are seeking leaders who code when it matters, who build systems and teams with equal conviction, and who view AI not as a trend but as a fundamental shift in how great software is built.


THE OPPORTUNITY AT A GLANCE :


AI-First Engineering Culture :

  • Own AI adoption across your squads - from LLM tooling integration to automation-first delivery workflows. Make AI a default, not an afterthought.


Hands-On Engineering Leadership :

  • Stay close to the code. Lead architecture reviews, unblock engineers, and set the technical bar - not just the management agenda.


People & Org Builder :

  • Grow engineers into leaders. Build squads of 615 across functions. Drive hiring, career frameworks, and a culture of psychological safety.


KEY RESPONSIBILITIES :


1. Hands-On Technical Engagement :

  • Remain deeply embedded in the technical work participate in design reviews, architecture decisions, and critical code reviews
  • Set and uphold the engineering quality bar : performance benchmarks, security standards, test coverage, and release quality
  • Provide technical direction on backend platform strategy, API design, service decomposition, and data architecture
  • Identify and resolve systemic technical debt and architectural risks across team-owned services
  • Unblock engineers by diving into complex problems debugging, pair programming, and system analysis when it matters
  • Own key technical decisions in collaboration with Tech Leads and Principal Engineers; balance pragmatism with long-term sustainability


2. AI Adoption, Integration & Transformation (2026 Mandate) :

  • Define and execute the team's AI adoption roadmap - from developer tooling to product-facing AI features
  • Champion the integration of GenAI tools (GitHub Copilot, Cursor, Claude, ChatGPT) across the full engineering workflow coding, testing, documentation, incident response
  • Embed LLM-powered capabilities into the product : recommendation engines, intelligent search, conversational interfaces, content generation, and predictive systems
  • Lead evaluation and adoption of AI-assisted SDLC practices : automated code review, AI-generated test suites, intelligent observability, and anomaly detection
  • Partner with Data Science and ML Platform teams to productionise ML models with robust MLOps pipelines
  • Build team literacy in prompt engineering, RAG (Retrieval-Augmented Generation), and AI agent frameworks
  • Create an experimentation culture : run structured AI pilots, measure productivity impact, and scale what works
  • Stay ahead of the AI tooling landscape and advise senior leadership on strategic AI investments and engineering implications


3. People Leadership & Team Development :

  • Lead, manage, and grow squads of 6 - 15 engineers across seniority levels (L2 through L6 / Junior through Staff)
  • Conduct structured 1 : 1s, career growth conversations, and development planning with every direct report
  • Design and execute personalised AI upskilling programmes ensure every engineer develops practical AI fluency by end of 2026
  • Build and maintain a high-performance team culture : clarity of ownership, accountability, fast feedback loops, and psychological safety
  • Drive performance management fairly and rigorously recognise top performers, manage underperformance constructively
  • Lead technical hiring end-to-end : define job requirements, conduct bar-raising interviews, and make data-driven hire decisions
  • Contribute to engineering career frameworks and level definitions in partnership with the VP / Director of Engineering


4. Engineering Delivery & Execution Excellence :

  • Own end-to-end delivery for multiple product squads from planning and scoping through production release and post-launch stability
  • Implement and refine agile delivery frameworks (Scrum, Kanban, Shape Up) calibrated to squad needs and product cadence
  • Drive predictable delivery : maintain healthy sprint velocity, manage WIP limits, and ensure dependency resolution across teams.
  • Establish and own engineering KPIs : DORA metrics (deployment frequency, lead time, MTTR, change failure rate), uptime SLOs, and velocity trends
  • Lead incident management : build blameless post-mortem culture, own RCA processes, and drive systemic reliability improvements
  • Balance technical debt repayment with feature velocity negotiate prioritisation transparently with Product leadership


5. Strategic Leadership & Cross-Functional Influence :

  • Serve as the primary engineering partner for Product, Design, Data, and Business stakeholders translate ambiguity into executable engineering plans
  • Participate in quarterly roadmap planning, capacity forecasting, and OKR definition for engineering teams
  • Represent engineering in leadership forums articulate technical constraints, risks, and opportunities in business terms
  • Contribute to org-wide engineering strategy : platform investments, build-vs-buy decisions, and shared infrastructure priorities
  • Build relationships across geographies (Mumbai HQ + distributed teams) to maintain alignment and delivery cohesion
  • Act as a culture carrier and ambassador for engineering excellence, innovation, and responsible AI use


AI TRANSFORMATION LEADERSHIP 2026 EXPECTATIONS :


In 2026, Engineering Managers at this organisation are expected to be active architects of AI transformation not passive observers. The following outlines the specific AI leadership expectations for this role :


AI Developer Productivity

  • Drive measurable uplift in developer velocity through AI tooling adoption. Target : 30%+ reduction in code review cycle time and 40%+ increase in test coverage automation by Q3 2026.


LLM & GenAI Product Features

  • Own delivery of GenAI-powered product capabilities : intelligent content, semantic search, personalisation, and conversational UX in production, at scale.


AI-Augmented Observability

  • Implement AI-driven monitoring and anomaly detection pipelines. Reduce MTTR by leveraging predictive alerting, intelligent runbooks, and auto-remediation scripts.


Team AI Fluency :

  • Build mandatory AI literacy across all engineering levels.
  • Every engineer understands prompt engineering basics, AI ethics guardrails, and responsible AI deployment practices.


Responsible AI Governance :

  • Partner with Security, Legal, and Data Privacy to ensure all AI deployments meet compliance standards, bias mitigation requirements, and explainability benchmarks.


TECHNOLOGY STACK & DOMAIN FAMILIARITY REQUIRED :


  • Languages: Java/ Go/ Python/ Node.js /PHP /Rust (must be hands-on in at least 2)
  • Cloud: AWS / GCP / Azure (multi-cloud exposure strongly preferred)
  • AI & GenAI: OpenAI / Anthropic / Gemini APIs /LangChain /LlamaIndex / RAG / Vector DBs / GitHub
  • Copilot: Cursor /Hugging Face
  • Containers: Docker /Kubernetes /Helm /Service Mesh (Istio / Linkerd)
  • Databases: PostgreSQL /MongoDB / Redis / Cassandra / Elasticsearch / Pinecone (Vector DB)
  • Messaging: Apache Kafka /RabbitMQ /AWS SQS/SNS /Google Pub/Sub
  • MLOps & DataOps: MLflow /Kubeflow / SageMaker / Vertex AI /Airflow /dbt
  • Observability: Datadog /Prometheus /Grafana /OpenTelemetry / Jaeger /ELK Stack
  • CI/CD & IaC: GitHub Actions ArgoCD / Jenkins / Terraform /Ansible /Backstage (IDP)


QUALIFICATIONS & CANDIDATE PROFILE :

Education :

  • B.E. / B.Tech or M.E. / M.Tech from a Tier-I or Tier-II Institution - CS, IS, ECE, AI/ML streams strongly preferred
  • Demonstrated engineering depth and leadership impact may complement institution pedigree


Experience :

  • 10 to 14 years of progressive engineering experience, with at least 3 years in a formal Engineering Manager or equivalent people-leadership role
  • Proven track record of managing and scaling engineering teams (615+ engineers) in a fast-growing SaaS or digital product environment
  • Hands-on backend engineering background must be able to read, write, and critique production code
  • Direct experience driving AI/ML feature delivery or AI tooling adoption within engineering organisations
  • Exposure across start-up, mid-size, and large-scale product organisations, preferred adaptability is a core requirement
  • Strong CS fundamentals: distributed systems, algorithms, system design, and software architecture
  • Demonstrated career stability minimum of 2 years of average tenure per organisation.


The Ideal Engineering Manager in 2026 :

  • Leads with context, not control, empowers engineers while maintaining accountability and quality
  • Is fluent in both people language and technical language, switches registers naturally with engineers and executives alike
  • Sees AI as a force multiplier for the team, not a threat. Actively experiments with and advocates for AI tooling
  • Measures success by team outcomes, not personal output. Takes pride in what the team ships, not what they build alone
  • Creates feedback loops obsessively between product and engineering, between seniors and juniors, between metrics and decisions
  • Has strong opinions, loosely held, brings conviction to discussions but updates on evidence
  • Invests in engineering excellence as seriously as delivery velocity knows that quality and speed are not opposites


WHY THIS ROLE STANDS APART :


AI Transformation at Scale :

  • Lead one of the most significant AI adoption programmes in India's digital media sector.
  • Our decisions will shape how hundreds of engineers work in 2026 and beyond.


Hands-On & Strategic Balance :

  • A rare EM role that actively encourages technical depth.
  • Stay close to the code while owning the people agenda - the best of both worlds.


Established Platform, Real Scale :

  • 5001,000 engineers, proven product-market fit, and the org maturity to execute.
  • This is not a greenfield startup gamble it is a serious company with serious ambition.


Clear Leadership Growth Path :

  • A visible, direct path toward Director / VP of Engineering.
  • Senior leadership is invested in growing its next generation of technology executives.


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Job Description :

We are currently building a next generation consumer tech product at the intersection of AI ML through Mobile and Commerce. The product requires building proprietary frameworks using latest technologies.

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  4. Work independently or with minimal supervision and utilize knowledge, experience and judgment to accomplish well defined goals

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  6. You have experience in identifying, debugging and resolving complex production issues End to End ownership of various applications and microservices

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1. You work with a team of passionate folks who love design and technology 2. Immense learning and growth opportunities in small, multi functional, tightly

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B.Tech/ MCA in Computer Science or equivalent 

About QuHu

QuHu is an audio first content platform where users can create, share & distribute their content and the discovery happens via a feed based on interest graph. We aim to build an audio ecosystem with a global presence consisting of audio-based social networks and audio communities.

At QuHu, we want to cultivate a vibrant and growing online UGC audio community and interactive audio entertainment platform where users are encouraged to create, share, discover and enjoy audio, and experience immersive and diversified entertainment features through audio. QuHu envisions a global audio ecosystem – a place where everyone can be connected through voices and across cultures.

The two pillars around which QuHu is built are:

Users - for whom we want to solve the problem of discovery basis interest (algorithmically driven feed) and provide an impressive experience through audio- bites (short content), live audio, audio rooms & audio games.

Creators - for whom we want to make creation & editing a seamless process through a suite of 'creator tools' like sound mixing, trim, pitch shifter, voicemojis, voice filters, noise reduction, etc & help them monetise

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Shubham Vishwakarma

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