Role Summary

We are hiring Senior Engineers who combine solid software engineering fundamentals with proven proficiency in AI-assisted development. This role is designed for engineers who have actively used AI coding tools (such as Cursor, Claude Code, Codex CLI only) for at least one year and can leverage these capabilities to ship higher-quality code faster. You will be embedded in product engineering squads, leading feature development, mentoring junior engineers, and championing AI-first development practices across the team.

What Makes This Role Different

This is not an AI research role - it is a core engineering role for engineers who use AI as a force multiplier. We expect you to:

• Use AI coding assistants daily to accelerate development without sacrificing code quality.
• Critically evaluate AI-generated code for correctness, security vulnerabilities, and maintainability.
• Share best practices for AI-assisted workflows with the broader engineering team.
• Help define team standards for responsible and effective AI tool adoption.

Key Responsibilities

1  Feature Engineering & Delivery

• Design, build, and ship production-quality features across the full stack or within your domain (backend, frontend, platform, or data).
• Leverage AI coding assistants to write, refactor, document, and test end-to-end code efficiently.
• Translate product requirements and technical specifications into clean, maintainable implementations.
• Lead feature squads for medium-complexity initiatives from design through deployment.
• Participate in and drive sprint planning, backlog grooming, and technical estimation sessions.

2  AI-Augmented Development Practices

• Champion the use of AI pair-programming tools (Copilot, Cursor, Claude, etc.) across the engineering org.
• Develop and document internal guidelines for effective AI prompt engineering within coding workflows.
• Conduct training sessions or knowledge-share presentations on maximising productivity with AI tools.
• Critically audit AI-generated code for logic errors, security issues, and performance anti-patterns before merging.
• Stay updated on the latest AI development tooling and evaluate new tools for team adoption.

3  Code Quality & Engineering Excellence

• Write testable, modular, and well-documented code following the team's style guides and design principles.
• Drive test-driven development (TDD) and maintain code coverage targets.
• Perform thorough code reviews with constructive feedback; uphold engineering standards.
• Identify and address technical debt proactively; contribute to architecture improvements.
• Participate in RCA (root cause analysis) for production incidents; implement lasting fixes.

4  Architecture & Technical Design

• Contribute to system design discussions, proposing solutions with appropriate trade-off analysis.
• Create and maintain technical design documents (TDDs), ADRs (Architecture Decision Records), and API contracts.
• Evaluate and adopt relevant third-party libraries, APIs, and SaaS tools with a security-first mindset.
• Collaborate with platform / DevOps teams on observability, CI/CD pipelines, and infrastructure-as-code.

5  Mentoring & Team Growth

• Mentor 1–2 mid-level engineers; conduct regular 1:1 technical coaching sessions.
• Onboard new team members by sharing codebase context, tooling setup, and team practices.
• Contribute to a culture of psychological safety, learning from failures, and continuous improvement.

6  Cross-functional Collaboration

• Work closely with Product Managers, Designers, and Operations to deliver delightful, high-quality user experiences.
• Coordinate with data and AI/ML teams to integrate model endpoints, APIs, and AI features into product surfaces.
• Participate in customer-facing escalations where deep technical expertise is required.

Required Qualifications

1  Education

• Bachelor's degree in Computer Science, Software Engineering, or a related field.
• Candidates without a degree but with a strong portfolio and demonstrable project history will be considered.

2  Experience

• 3 – 5 years of professional software engineering experience in a product-focused environment.
• Minimum 1 year of active, hands-on experience using AI coding tools in professional work (not just personal projects).
• Track record of shipping production features end-to-end with measurable business impact.

3  Technical Skills — Core Engineering

• Languages: Proficiency in at least one of — Python, TypeScript/JavaScript, Java, Go, or Kotlin.
• Web / API: REST, GraphQL, gRPC; familiarity with microservices and event-driven architectures.
• Databases: SQL (PostgreSQL, MySQL) and NoSQL (MongoDB, Redis, DynamoDB).
• Cloud: AWS, GCP, or Azure — compute, storage, serverless, and managed services.
• DevOps: Docker, Kubernetes, CI/CD (GitHub Actions, Jenkins, CircleCI); IaC basics (Terraform/Pulumi).
• Testing: Unit, integration, and e2e testing frameworks; TDD/BDD familiarity.
• Version Control: Git, branching strategies (GitFlow, trunk-based), PR workflows.

4  AI Tooling Skills (Mandatory)

• Demonstrated proficiency with at least one AI coding assistant (Cursor IDE, Claude Code, Codex CLI).
• Ability to craft effective prompts for code generation, refactoring, debugging, and documentation tasks.
• Experience reviewing and validating AI-generated code for correctness and security.
• Understanding of limitations of LLM-based coding tools (hallucinations, context window, license risks).

5  Nice to Have

• Contributions to open-source projects.
• Experience building or integrating AI/ML features (e.g., calling LLM APIs, embedding models, RAG pipelines).
• Familiarity with agentic coding frameworks (LangChain, LlamaIndex, AutoGen, CrewAI).
• Experience in a startup or scale-up environment with rapid iteration cycles.
• Knowledge of web security (OWASP Top 10, secure coding practices).

Behavioural Competencies

• AI-First Mindset: Naturally reaches for AI tools to accelerate tasks while maintaining engineering rigour.
• Ownership: Takes end-to-end accountability — from design to deployment to monitoring.
• Pragmatism: Balances perfect with shipped; knows when to iterate vs. over-engineer.
• Mentorship: Invests in the growth of peers and junior colleagues.
• Communication: Writes clearly (code comments, docs, Slack) and articulates trade-offs confidently.
• Curiosity: Continuously explores new tools, languages, and architectural patterns.
• Collaboration: Works well in cross-functional squads; builds trust quickly.

Role Summary

We are seeking a Lead Engineer, AI Systems to serve as the technical anchor across our AI-augmented engineering organisation. This role bridges our Senior AI Coding Engineers, the AI/ML Developer (SLM Specialist), and the Agentic Systems intern cohort. You will set technical direction, own cross-cutting architectural decisions, and champion the responsible, high-impact adoption of AI-assisted development practices across the entire engineering function.

You will remain hands-on with code while simultaneously shaping how the wider team builds, evaluates, and ships AI-powered products.

Key Responsibilities

1  Technical Vision & Architecture

• Define and own the end-to-end technical architecture for AI Systems — spanning product feature surfaces, model inference APIs, and agentic toolchains.
• Drive Architecture Decision Records (ADRs), system design reviews, and RFC processes across squads.
• Establish standards for integrating SLM/LLM model endpoints into product surfaces built by the Senior Engineering team.
• Evaluate emerging AI infrastructure patterns (RAG, agentic orchestration, vector stores, model serving) and guide adoption decisions.
• Own the technical roadmap for AI tooling, developer productivity, and model integration layers.

2  Cross-Squad Technical Leadership

• Act as the primary technical liaison between the AI/ML Developer (model side) and Senior Engineers (product side), ensuring smooth API contracts, evaluation loops, and deployment handoffs.
• Provide technical direction to Agentic Systems interns, reviewing designs, code, and agentic pipeline implementations.
• Unblock senior engineers on hard architectural or integration challenges that span squad boundaries.
• Run cross-team design reviews, architecture syncs, and engineering guild sessions.

3  AI-Augmented Engineering Excellence

• Define and maintain the organisation’s standards for AI-assisted development — covering context engineering, AI code review protocols, context management, and tool evaluation criteria.
• Maintain and evolve the internal AI tooling playbook (Cursor IDE, Claude Code, Codex CLI, and emerging tools).
• Evaluate new AI coding tools, agentic frameworks (LangChain, LlamaIndex, CrewAI, AutoGen), and developer-productivity platforms; produce adoption recommendations with measured trade-offs.
• Conduct structured audits of AI-generated code across squads for correctness, security, and maintainability.

4  Hands-On Engineering

• Remain an active contributor: own critical-path features, prototype architectural spikes, and build shared infrastructure components used across squads.
• Personally drive resolution of the most complex production incidents and root-cause analyses.
• Review and merge high-impact PRs; maintain the highest code review quality bar on the team.
• Own observability and reliability for AI inference and MLOps integration layers in production.

5  Mentoring & Talent Development

• Mentor Senior Engineers, the AI/ML Developer, and interns through technical coaching, design feedback, and stretch assignments.
• Lead hiring panels and technical interviews; help define and uphold the engineering hiring bar.
• Contribute to onboarding frameworks that embed AI-first practices from day one.
• Model a culture of rigorous experimentation, psychological safety, and continuous improvement.

6  Stakeholder & Product Collaboration

• Partner with the Director of Engineering and Product leadership to translate product strategy into a phased technical roadmap.
• Present architectural proposals and trade-off analyses to engineering leadership and executive stakeholders as required.
• Coordinate with DevOps/Platform teams on GPU/TPU compute provisioning, CI/CD for model pipelines, and cloud cost optimisation.

Required Qualifications

1  Education

• Bachelor’s or Master’s degree in Computer Science, or a related field.
• Candidates without a degree but with a compelling portfolio demonstrating scope and impact at staff/lead level will be considered.

2  Experience

• 6 – 8 years of professional software engineering experience in product-focused environments.
• Minimum 2 years in a formal or de-facto technical lead / staff engineer capacity across multiple squads or systems.
• Minimum 8-12 months of active, hands-on experience with AI coding tools in a professional engineering setting.
• Proven track record of shipping production systems with measurable business impact at scale.
• Demonstrated experience collaborating closely with ML/AI model teams on integration, deployment, and evaluation.

3  Technical Skills — Core Engineering

• Languages: Expert proficiency in at least two of — Python, TypeScript/JavaScript, Go.
• Architecture: Microservices, event-driven systems, API design (REST, GraphQL, gRPC), distributed systems fundamentals.
• Databases: SQL (PostgreSQL, MySQL) and NoSQL (MongoDB, Redis); vector databases (FAISS, Pinecone, Weaviate).
• Cloud: AWS, GCP, or Azure — compute, storage, serverless, managed ML services (SageMaker, Vertex AI).
• DevOps: Docker, Kubernetes, CI/CD (GitHub Actions, Jenkins); IaC (Terraform/Pulumi); observability stacks.
• Testing: TDD/BDD; unit, integration, and e2e frameworks; model evaluation pipelines.

4  AI / ML Integration Skills (Mandatory)

• Demonstrated proficiency with AI coding assistants (Cursor IDE, Claude Code, Codex CLI) in daily professional workflows.
• Experience designing and consuming LLM/SLM inference APIs; understanding of model serving, latency, and cost trade-offs.
• Hands-on familiarity with RAG architectures, vector stores, and retrieval pipelines.
• Ability to define and enforce AI code quality standards across an engineering team.
• Understanding of LLM limitations: hallucinations, context window constraints, prompt injection risks, and licensing considerations.

5  Technical Skills — Nice to Have

• Experience with SLM/LLM training or fine-tuning pipelines (SFT, RLHF, LoRA/QLoRA).
• Familiarity with agentic frameworks (LangChain, LlamaIndex, AutoGen, CrewAI) and multi-step reasoning pipelines.
• Contributions to open-source ML or developer tooling projects.
• Knowledge of OWASP Top 10, secure coding, and AI-specific security risks (prompt injection, model exfiltration).
• Prior experience in a high-growth startup or scale-up environment with rapid iteration cycles.

Behavioural Competencies

• AI-First Mindset: Defaults to AI tools to accelerate work while maintaining rigorous quality standards; actively pushes the team’s AI capability forward.
• Systems Thinking: Sees the full picture — how model outputs, product surfaces, and infrastructure interdepend; anticipates second-order effects of architectural choices.
• Ownership: Takes end-to-end responsibility from design through production; doesn’t hand off problems, solves them.
• Influence Without Authority: Earns trust through technical credibility; drives alignment through persuasion, data, and well-reasoned proposals.
• Communication: Writes clear design docs, ADRs, and post-mortems; articulates complex trade-offs for engineering peers and non-technical stakeholders.
• Mentorship: Actively invests in the growth of engineers at all levels; gives direct, constructive feedback.
• Pragmatism: Balances the ideal with the shipped; knows when to iterate vs. refactor vs. rewrite.
• Curiosity: Continuously explores emerging research, tools, and patterns — and brings those learnings back to the team.

About Payoneer 

Founded in 2005, Payoneer is the global financial platform that removes friction from doing business across borders, with a mission to connect the world’s underserved businesses to a rising global economy. We’re a community with over 2,500 colleagues all over the world, working to serve customers and partners in over 190 countries and territories. 

By taking the complexity out of the financial workflows–including everything from global payments and compliance to multi-currency and workforce management, to providing working capital and business intelligence–we give businesses the tools they need to work efficiently worldwide and grow with confidence. 

Role summary 

We’re looking for a Principal Architect who is a tech-enthusiast with a drive for excellence, and an out-of-the-box mindset to satisfy business needs in a complex payment solution environment. 

Location: Gurgaon-India 

Hybrid - Full-time 

What You’ll Do 

• You will be a core member of the Cloud Modernization initiative, a high-impact engineering function responsible for transforming our technology backbone into a modern, cloud-native platform. 
• You will operate at the intersection of cloud architecture and enterprise modernization, leading critical initiatives to migrate, modernize, and re-architect legacy platforms into scalable, secure, and highly automated cloud-native systems. 
• You will lead initiatives from a technical front, defining target architectures, establishing modernization patterns, and driving execution across engineering teams. You will design and implement cloud-native solutions, modern infrastructure platforms, and secure cloud environments that can support global-scale workloads. 
• This role operates in a mission-driven model, where you will engage with multiple teams to accelerate modernization, unblock critical initiatives, and establish patterns and platforms that can be adopted broadly across the organization. 
• You will work closely with architecture, platform, infrastructure, security, and product teams to modernize legacy systems, migrate databases and applications to the cloud, introduce modern DevOps and platform engineering practices, and raise the overall cloud maturity of the organization. 
• Your work will directly shape the company’s future cloud platform and engineering velocity. 

Who You Are 

• You are a seasoned Cloud and Modernization Architect with a strong sense of ownership and accountability. You are comfortable operating in complex enterprise environments and driving large-scale transformation initiatives. 
• You bring deep expertise across cloud platforms, infrastructure, databases, and DevOps, and can translate legacy architectures into modern, scalable, and cloud-native systems. 
• You balance long-term architectural vision with pragmatic execution and understand how to modernize systems safely and incrementally. 
• You embrace change and continuously adapt to evolving technologies, architectures, and organizational needs. You are proactive, curious, and comfortable making architectural decisions in ambiguous environments. 
• You thrive in cross-team environments and influence teams through technical leadership, clarity, and strong execution. 
• You are impact-driven, not territory-driven, and measure success by how effectively you modernize systems, enable teams, and improve the organization’s overall cloud maturity. 

Key skills and competencies 

• 10+ years of experience in cloud architecture, infrastructure, or platform engineering 
• Deep hands-on experience with public cloud platforms, preferably AWS 
• Proven experience leading cloud migration and modernization of enterprise systems 
• Strong experience designing cloud architecture including compute, storage, networking, and security 
• Strong experience with Infrastructure as Code, preferably Terraform or CloudFormation 
• Experience with cloud networking, VPC design, private connectivity, and secure architectures 
• Experience with relational databases such as PostgreSQL, MySQL, or Aurora 
• Experience with NoSQL databases such as DynamoDB, MongoDB, or similar 
• Experience with containers and Kubernetes, preferably EKS 
• Experience building and operating CI/CD pipelines and modern DevOps practices 
• Experience modernizing legacy systems into microservices or cloud-native architectures 
• Experience with high availability, scalability, and disaster recovery design 
• Experience working in enterprise environments with strong security and compliance requirements 
• B.S. in computer science or equivalent 

The Payoneer Ways of Working Act as our customer’s partner on the inside 

Learning what they need and creating what will help them go further. 

Continuously improve 

Always striving for a higher standard than our last. 

Do it. Own it. 

Being fearlessly accountable in everything we do. 

Build each other up 

Helping each other grow, as professionals and people. 

If this sounds like a business, a community, and a mission you want to be part of, apply today. 

We are committed to providing a diverse and inclusive workplace. Payoneer is an equal opportunity employer, and all qualified applicants will receive consideration for employment no matter your race, color, ancestry, religion, sex, sexual orientation, gender identity, national origin, age, disability status, protected veteran status, or any other characteristic protected by law. If you require reasonable accommodation at any stage of the hiring process, please speak to the recruiter managing the role for any adjustments. Decisions about requests for reasonable accommodation are made on a case-by-case basis. 

#LI-AK1

About WPP Media 

WPP is the creative transformation company. We use the power of creativity to build better futures for our people, planet, clients and communities. For more information, visit wpp.com. 

WPP Media is WPP’s global media collective. In a world where media is everywhere and in everything, we bring the best platform, people, and partners together to create limitless opportunities for growth. For more information, visit wppmedia.com 

At WPP Media, we believe in the power of our culture and our people. It’s what elevates us to deliver exceptional experiences for both our clients and each other. In this role it will be critical to embrace WPP & WPP Media’s shared core values: 

• Be Extraordinary by Leading Collectively to Inspire transformational Creativity. 
• Create an Open environment by Balancing People and Client Experiences by Cultivating Trust. 
• Lead Optimistically by Championing Growth and Development to Mobilize the Enterprise. 

Skills and Experience:

If this opportunity looks right for you, we are looking for candidates who have:

Essential Criteria

• Proven experience (5+ years) as a Backend Software Developer, with a strong portfolio of projects involving data processing and API development.
• Proficiency in one or more backend programming languages (e.g., Python, Java, Go, Node.js). Python is highly preferred given its prevalence in data science and ML.
• Strong experience with cloud platforms, particularly Google Cloud Platform (GCP), including services like Cloud Functions, Cloud Run, App Engine, Pub/Sub, Cloud Storage, and BigQuery.
• Demonstrable experience in designing, building, and maintaining RESTful APIs and microservices.
• Solid understanding of database technologies, both relational (e.g., PostgreSQL, MySQL) and NoSQL (e.g., MongoDB, Firestore), and experience with data modelling.
• Experience with data pipeline tools and concepts (e.g., Apache Beam/Dataflow, Airflow) for ETL/ELT processes.
• Familiarity with version control systems (e.g., Git) and agile development methodologies.
• Basic understanding of machine learning concepts and how to integrate ML models into backend systems.
• Basic understanding of the total marketing process and the strategic role of insights and media.
• An appreciation for how data insights are used in various media channels (e.g., paid search, programmatic display, social media, SEO) to inform strategy.
• Excellent problem-solving skills and attention to detail.
• Experience working with off-shore or distributed teams is highly desirable.
• Experience integrating data into Google BigQuery from various sources, including direct API connections and data integration platforms (e.g., Adverity).
• Experience with leveraging AI/ML capabilities within the GCP ecosystem, such as connecting to large language models (e.g., Google's Gemini API) or utilising platforms like Vertex AI to enrich and analyse data stored in BigQuery.

Preferred Criteria

• Experience with stream processing technologies (e.g., Kafka, Pub/Sub).
• Knowledge of containerization technologies (e.g., Docker, Kubernetes).
• Experience with CI/CD pipelines.
• Familiarity with data security and privacy best practices.
• Experience in the media, advertising, or marketing technology (AdTech/MarTech) industry.
• Certifications in relevant cloud technologies.

Life at WPP Media & Benefits:

Our passion for shaping the next era of media includes investing in our employees to help them do their best work, and we’re just as committed to employee growth as we are to responsible media investment. WPP Media employees can tap into the global WPP Media & WPP networks to pursue their passions, grow their networks, and learn at the cutting edge of marketing and advertising. We have a variety of employee resource groups and host frequent in-office events showcasing team wins, sharing thought leadership, and celebrating holidays and milestone events. Our benefits include access to internal learning platforms, certifications, training sessions, life insurance, wellness programs, significant paid time off, preferential partner discounts, employee mental health awareness day and more.

WPP Media is an equal opportunity employer and considers applicants for all positions without discrimination or regard to particular characteristics. We are committed to fostering a culture of respect in which everyone feels they belong and has the same opportunities to progress in their careers.
 
 We believe the best work happens when we're together, fostering creativity, collaboration, and connection. If you require accommodation or flexibility, please discuss this with the hiring team during the interview process.

Research shows that candidates from underrepresented backgrounds often don't apply for roles if they don't meet all the criteria.  At WPP Media, we strongly encourage you to apply if you’re interested: we'd love to know how you can positively impact our team with your experience!

As an Equal Opportunities Employer, we believe that diversity is vital and positively influences the environment in which we operate. We are committed to fostering a diverse and inclusive work environment that is free of discrimination, harassment or bullying. Race, color, ancestry, religion, gender, gender identity, national origin, sexual orientation, age, marital status or disability status have no bearing on our hiring decisions, and we encourage all applicants.

We view everyone as an individual and we understand that inclusion is more than just diversity – it’s about belonging. We celebrate the fact that everyone is unique and that’s what makes us so good at what we do. We pride ourselves on being a company that embraces difference and truly represents the global clients we work with.

Life at WPP Media & Benefits 

Our passion for shaping the next era of media includes investing in our employees to help them do their best work, and we’re just as committed to employee growth as we are to responsible media investment. WPP Media employees can tap into the global WPP Media & WPP networks to pursue their passions, grow their networks, and learn at the cutting edge of marketing and advertising. We have a variety of employee resource groups and host frequent in-office events showcasing team wins, sharing thought leadership, and celebrating holidays and milestone events. Our benefits include competitive medical, group retirement plans, vision, and dental insurance, significant paid time off, preferential partner discounts, and employee mental health awareness days.   

WPP Media is an equal opportunity employer and considers applicants for all positions without discrimination or regard to characteristics. We are committed to fostering a culture of respect in which everyone feels they belong and has the same opportunities to progress in their careers.

We believe the best work happens when we're together, fostering creativity, collaboration, and connection. That's why we’ve adopted a hybrid approach, with teams in the office around four days a week. If you require accommodations or flexibility, please discuss this with the hiring team during the interview process. 

About Nanonets

Nanonets has a vision to help computers see the world starting with reading and understanding documents. Our product helps businesses automate document related workflows for enterprise office teams such as invoice data entry for AP teams, KYC automation for banks and insurance etc. Some of the companies we work with include Toyota, Boston Scientific, Bill.com and Entergy to name a few. 

We recently raised a series B round of $29 million. Now we’re on a mission to hire the very best and are committed to creating exceptional employee experiences where everyone is respected and has access to equal opportunity. 

Job description

At Nanonets, we are building AI-powered automation agents to eliminate manual healthcare admin tasks - helping customers streamline operations and deliver better patient care.

We are looking for a Full Stack Software Engineer who thrives in fast-paced startup environments, enjoys shipping impactful products quickly, and can work across the stack to bring our AI agents to life.

You’ll work with a small, high-performing team building production-grade AI agents - combining distributed systems, AI integration, and intuitive web platforms.

What You’ll do : 

• Design, develop, and deploy AI agent services that automate healthcare workflows.
• Build scalable APIs, backend services, and sleek frontend interfaces.
• Ship high-quality, maintainable code - fast.
• Collaborate closely with product and AI teams to iterate on agent workflows.
• Monitor, debug, and improve production systems continuously.

What we expect from you :

• 3-6 years of hands-on experience in full stack engineering.
• Experience working in a fast-moving startup, with a track record of shipping products quickly.
• Proficiency in at least one backend language (Go or Python) and one frontend framework (preferably React + TypeScript).
• Experience with using LLM APIs and LLM-based applications.
• Strong understanding of web architecture, distributed systems, APIs, and relational databases.
• Ability to write clean, testable code and solve production issues effectively.
• A builder’s mindset: ownership, initiative, and bias for action.

Nice to have :

• Familiarity with US healthcare or other regulated domains.
• Knowledge of DevOps practices, cloud infrastructure, and CI/CD pipelines.

Our Tech Stack :

• Backend: Go, Python
• Frontend: React, TypeScript
• Databases & Infra: PostgreSQL, Redis, AWS/GCP

Why join us ?

• Work on cutting-edge AI agents transforming the healthcare industry.
• Be part of a small, high-impact, no-bureaucracy team.
• Ship products that make a real-world difference for customers.
• Learn fast, grow fast - with competitive compensation & career growth opportunities.

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