Scientist - Natural Language Processing Engineer

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.

1) Be open to learn new frameworks like Hapi.JS , Typescript , Nest.JS

2) Strong DB concepts , and hands on knowledge on MongoDB , REDIS

3) Experience working with micro-services will be a plus

4) Experience working with JWT and IAM systems will be a plus

5) Experience working with Postman , Swagger will be a plus

6) TDD knowledge is an advantage and also working with Unit Test code and familiar with test code coverage concepts.

7) Strong operating system knowledge is a plus with knowledge of how to manage threads.

8) Working experience with RabbitMQ , Kafka will be a plus

9) Strong knowledge of JS internals is a must.

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

Senior BackEnd Engineer

The ideal candidate will have a strong background in building scalable applications, a deep understanding of back-end technologies, and experience with cloud infrastructure. As a Back End Engineer, you will be responsible for designing, developing, and maintaining a scalable workflow management system. You will work closely with cross-functional teams to build robust and efficient applications that meet the needs of our users. Your expertise in Scala, Python, AI Agents/APIs, and GCP will be crucial in ensuring our system is reliable, performant, and scalable.

Key Responsibilities:

Back-End Development:

• Build and maintain back-end services and APIs using Scala.
• Implement and optimize Orchestration workflow system involving database queries and operations.
• Build API integrations with Third Party APIs and services.
• Ensure robust and scalable server-side logic.

Cloud Integration:

• Deploy, manage, and monitor applications on Google Cloud Platform (GCP).
• Utilize GCP services to enhance application performance and scalability.
• Implement cloud-based solutions for data storage, processing, and analytics.

Collaboration And Communication:

• Work closely with cross-functional teams to define, design, and ship new features.
• Participate in code reviews and contribute to sharing team knowledge.
• Document development processes, coding standards, and project requirements.

Qualifications:

• Educational Background:
• Completed a masters/bachelor degree in Computer Science, Engineering, or a related field.
• Technical Skills:
• Proficiency in Scala programming language.
• Strong experience with React and ReactJS.
• Familiarity with Google Cloud Platform (GCP) and its services.
• Knowledge of front-end development tools and best practices.
• Understanding of RESTful API design and implementation.
• Soft Skills:
• Excellent problem-solving skills and attention to detail.
• Strong communication and collaboration abilities.
• Eagerness to learn and adapt to new technologies and challenges.

Preferred Qualifications:

• Experience with version control systems such as Git.
• Familiarity with CI/CD pipelines and DevOps practices.
• Understanding of workflow management systems and their requirements.
• Experience with containerization technologies like Docker.

Must have Skills

• Scala - 4 Years
• React.Js - 1 Years
• RESTful API - 4 Years
• Docker - 2 Years
• Python - 3 Years
• Artificial Intelligence - 2 Years

Software Engineer

Onsite - HSR Bangalore

6 Days work from Office (Flexible working hours)

Product is a PowerPoint AI assistant used by consulting companies and Fortune 500 teams. A typical professional spends 1 to 3 hours creating one slide. With Product company, they create a v1 of their entire deck in 10 minutes, and make changes like “turn this table to a chart” in seconds directly within PowerPoint.

In the next 2 years, our goal at company is to forever change the way business presentations are made.

Who are we?

• small, strong team of 5
• founders are CS graduates from IIT Kharagpur with a specialisation in AI
• work 6 days a week from our office in HSR Layout in Bangalore
• funded by Y Combinator and other amazing investors
• used by consulting companies and Fortune 500 teams

Your responsibilities (in order)

• Design, implement, test, and deploy full features
• Design and implement a robust infrastructure to enable rapid development and automated testing
• Look at usage data to iterate on features

What we’re looking for

• Undergraduate or master's in Computer Science or equivalent degree
• 2+ years of backend or DevOps software engineering experience
• Experience with TypeScript (JavaScript) or Python

You’ll be a good fit if

• You want to work on a product that can change the way a very large number of people work
• The chaos of high growth and things breaking is exciting to you
• You are a workaholic, looking to upskill faster than most people think is possible. This role is not a good fit for you if you’re looking to prioritise work-life balance.
• You prefer working in-person with other smart people who are excited and passionate about what they’re building
• You love solving very hard problems at a rapid pace. We discuss timelines in days or weeks, so you’ll constantly be expected to ship really high-quality work.

Perks

• Comprehensive health insurance for you and dependents
• Workstation enhancements
• Subscriptions to AI tools such as Cursor, ChatGPT, etc.

(If there's anything else we can do to make your work more enjoyable, just ask)

If you are interested in proceeding, we would be happy to move your profile to the next stage of the evaluation process.

Kindly share the following details to help us take this forward :

• Current CTC (Fixed + Variable):
• Expected CTC:
• Notice Period (If currently serving, please mention your Last Working Day)
• Details of any active offers in hand (if applicable)
• Expected/Available Date of Joining (if applicable)
• Attach Updated CV:
• Attach Github Link / Leet code link or other:
• Current Location:
• Preffered Location:
• Reason for job Change:
• Reason for relocation (if applicable):
• Are you comfortable with 6 days wfo (flexible working hours)?( Yes / No):
• 
  

Description :

Job Title : Python Engineer- AI Agents & Code Optimization

Experience : 2+ Years

Employment Type : Full-time

Location : Remote

About the Role :

We are looking for a hands-on Software Engineer to build and improve AI agents that work directly on our production code.

Your core responsibility will be to design and evolve a specialized AI agent that deeply understands our codebase and actively helps make it faster, cleaner, simpler, and cheaper to maintain.

This is not a research role. This is real work on real systems with real business impact.

How We Work :

- Business impact first : Cheaper, Faster, Better

- Simple beats complex always

- Small changes, shipped fast

- You own your work end-to-end

- First question is always : Do we even need this?

- Flat team, zero micromanagement

- Decisions can change adaptability matters

- No long PRDs : one clear goal ? discuss ? execute

- Ship, measure, improve, repeat

What You Will Do :

- Build and use AI agents to optimize, refactor, and remove code

- Feed logs, metrics, and performance data back into AI agents

- Profile applications and identify performance bottlenecks

- Optimize SQL queries and database usage

- Improve deployment pipelines and release processes

- Continuously improve internal AI tooling

- Work closely with infrastructure and production systems

Tech You Should Be Comfortable With :

You dont need to be an expert in everything, but you should be comfortable working with :

- Linux CLI (Required)

- Python

- PHP

- SQL (MySQL or MariaDB)

- Shell scripting

- Large Language Models (LLMs)

What Were Looking For :

- 2+ years of software engineering experience (or strong hands-on projects)

- Solid understanding of performance optimization

- Experience cleaning up legacy or messy codebases

- Practical profiling and debugging skills

- Comfortable working close to infrastructure and deployments

- Automation-first mindset

- Ability to explain technical decisions clearly and simply in English

Nice to Have :

- Experience building AI agents

- Exposure to large or long-running systems

- CI/CD or deployment automation experience

When You Join :

- Career Growth : You are expected to grow into a tech lead, entrepreneur, or highly skilled specialist

- Bleeding-Edge Tech : Hands-on experience with alpha/beta software, cutting-edge infrastructure, and top tier hardware

- Global Exposure : Work with a global team and directly with C-level leadership

- Real Impact : Your code directly solves real user problems and moves the company forward

We're looking for AI/ML enthusiasts who build, not just study. If you've implemented transformers from scratch, fine-tuned LLMs, or created innovative ML solutions, we want to see your work!

What You’ll Do

-Build autonomous AI agents using LangChain, LangGraph, and similar frameworks.

- Develop RAG pipelines with vector DBs like FAISS, Pinecone, or ChromaDB.

- Create FastAPI endpoints to expose agent functionality.

- Implement Model Context Protocol (MCP) for tool-agent integrations.

- Optimize prompts, workflows, and retrieval strategies for real performance.

- Contribute to new agentic AI design patterns and innovations.

Who Should Apply

We’re looking for freshers who are:

-Strong in Python and love experimenting with AI/ML projects.

- Familiar with one or more of these: LangChain/LangGraph, HuggingFace, PyTorch/TensorFlow, RAG pipelines.

- Active on GitHub with 2–3 well-documented projects (clean code + clear README).

- Curious, hands-on builders who want to learn by doing.

Bonus Points if you’ve dabbled with:

- LLM fine-tuning (LoRA, QLoRA), memory systems. AutoGen, CrewAI, MCP, or other agent frameworks.

- Docker, async programming, API integrations.

Education:

- Completed/Pursuing Bachelor's in Computer Science or related field

- Strong foundation in ML theory and practice

Apply if:

1. You have done projects using GenAI, Machine Learning, Deep Learning.
2. You must have strong Python coding experience.
3. Someone who is available immediately to start with us in the office(Hyderabad).
4. Someone who has the hunger to learn something new always and aims to step up at a high pace.

We value quality implementations and thorough documentation over quantity. Show us how you think through problems and implement solutions!

Should be highly Technical and hands-on experience in Artificial Intelligence and Machine learning and Python. Managing the successful delivery of projects by efficient planning and coordination.

KEY RESPONSIBILITIES OF THE POSITION :

• Create Technical Design for AI, Machine Learning, Deep Learning, NLP, NLU, NLG projects and implement the same in production.
• Solid understanding and experience of deep learning architectures and algorithms
• Working experience with AWS, most importantly AWS SageMaker, Aurora or MongoDB, Analytics and reporting.
• Experience solving problems in the industry using deep learning methods such as recurrent neural networks (RNN, LSTM), convolutional neural nets, auto-encoders, etc.
• Should have experience of 2-3 production implementations of machine learning projects.
• Knowledge of open-source libraries such as Keras, Tensor Flow, Pytorch
• Work with business analysts/consultants and other necessary teams to create a strong solution
• Should have in-depth understanding and experience of Data Science and Machine Learning projects using Python, R, etc. Skills in Java/C are a plus
• Should developing solutions using python in AI/ML projects
• Should be able to train and build a team of technical developers
• Desired to have experience as leads in designing and developing applications/tools using Microsoft technologies - ASP.Net, C#, HTML5, MVC
• Desired to have knowledge on any of the cloud solutions such as Azure or AWS
• Desired to have knowledge on any of container technology such as Docker
• Should be able to build strong relationships with project stakeholders

Keywords:

• Python
• Artificial Intelligence
• Machine Learning
• AWS
• Django
• NLP