Python Engineer (AI & Cloud)

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.

About Synorus

Synorus is building a next-generation ecosystem of AI-first products. Our flagship legal-AI platform LexVault is redefining legal research, drafting, knowledge retrieval, and case intelligence using domain-tuned LLMs, private RAG pipelines, and secure reasoning systems.

If you are passionate about AI, legaltech, and training high-performance models — this internship will put you on the front line of innovation.

Role Overview

We are seeking passionate AI/LLM Engineering Interns who can:

• Fine-tune LLMs for legal domain use-cases
• Train and experiment with open-source foundation models
• Work with large datasets efficiently
• Build RAG pipelines and text-processing frameworks
• Run model training workflows on Google Colab / Kaggle / Cloud GPUs

This is a hands-on engineering and research internship — you will work directly with senior founders & technical leadership.

Key Responsibilities

• Fine-tune transformer-based models (Llama, Mistral, Gemma, etc.)
• Build and preprocess legal datasets at scale
• Develop efficient inference & training pipelines
• Evaluate models for accuracy, hallucinations, and trustworthiness
• Implement RAG architectures (vector DBs + embeddings)
• Work with GPU environments (Colab/Kaggle/Cloud)
• Contribute to model improvements, prompt engineering & safety tuning

Must-Have Skills

• Strong knowledge of Python & PyTorch
• Understanding of LLMs, Transformers, Tokenization
• Hands-on experience with HuggingFace Transformers
• Familiarity with LoRA/QLoRA, PEFT training
• Data wrangling: Pandas, NumPy, tokenizers
• Ability to handle multi-GB datasets efficiently

Bonus Skills

(Not mandatory — but a strong plus)

• Experience with RAG / vector DBs (Chroma, Qdrant, LanceDB)
• Familiarity with vLLM, llama.cpp, GGUF
• Worked on summarization, Q&A or document-AI projects
• Knowledge of legal texts (Indian laws/case-law/statutes)
• Open-source contributions or research work
• 
  

What You Will Gain

• Real-world training on LLM fine-tuning & legal AI
• Exposure to production-grade AI pipelines
• Direct mentorship from engineering leadership
• Research + industry project portfolio
• Letter of experience + potential full-time offer
• 
  

Ideal Candidate

• You experiment with models on weekends
• You love pushing GPUs to their limits
• You prefer research + implementation over theory alone
• You want to build AI that matters — not just demos

Location - Remote

Stipend - 5K - 10K

This is a fully remote opportunity

About Us:

We at Ascendeum provide Data and AdTech strategy consultation to businesses worldwide. We started our journey with private funding and has been operating profitably since 2015. We are a lean team of 50+ highly productive and smart people spread across various parts of India who have been consistently delivering intelligent solutions that enable enterprise-level websites and apps to maximize their digital advertising returns.

Job Details:

We are looking for an analytical, results-driven Back-end Engineer who holds a passion to troubleshoot and improve current back-end applications and processes. The Back- end Developer will use his or her understanding of programming languages and tools to analyze current codes and industry developments, formulate more efficient processes, solve problems, and create a more seamless experience for users.

Job Responsibilities:

• Compile and analyze data, processes, and codes to troubleshoot problems and identify areas for improvement.
• Collaborating with the front-end developers and other team members to establish objectives and design more functional, cohesive codes to enhance the user experience.
• Developing ideas for new programs, products, or features by monitoring industry developments and trends.
• Recording data and reporting it to proper parties, such as clients or leadership.
• Participating in continuing education and training to remain current on best practices, learn new programming languages, and better assist other team
• members.
• Taking lead on projects, as needed.

Desired Skills and Experience:

• Bachelor’s degree in computer programming, computer science, or a related field.
• Solid experience specializing in developing and managing back-end systems for enterprise-grade applications.
• Strong command on Python and databases such as MySQL.
• Strong understanding of the web development cycle and programming
• techniques and tools.
• Focus on efficiency, user experience, and process improvement.
• Excellent project and time management skills.
• Strong problem solving and verbal and written communication skills.
• Ability to work independently or with a group.

Key Skills:

1. One or more of Python/PHP/Ruby/NodeJS/Java

2. Sound object-oriented skills, including strong design patterns knowledge

2. REST APIs

3. MVC architecture

4. MySQL/PostgreSQL

5. Exp with at least 1 NoSQL databases MongoDB/Memcache/Redis/

6. Exp with search technologies Elasticsearch/Solr

7. Exp building messaging based asynchrounous systems RabbitMQ/Kafka/SQS/Celery will be added advantage

8. Exp with Django/Flask frameworks will be added advantage

9. Knowledge of software best practices like Test-Driven Development (TDD) and Continuous Integration (CI) will be added adnavtage

Requirements:

1. Developing software solutions in conjunction with Relational theory, Rest APIs and NoSQL database technologies

2. Knowledge of cloud based technologies in AWS or Azure will be added advantage

3. Understanding of RDBMS technologies like MySQL, PostgreSQL.

4. Hands-on with Version control systems (GIT, SVN) and Unix/Ubuntu.

5. Experience in requirement analysis, HLD, LLD, unit & integration testing.

6. Good hands on experience in debugging application issues

TL;DR

1) Top performer in the company

2) Has worked with product based startup company

3) Ambitious and hardworking