Job responsibilities

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About Thoughtworks

We’re looking for a Full Stack Engineer who expects more from their career. This role offers an opportunity to build scalable, high-performance solutions in the engineering team, enhance code quality and engineering excellence, and contribute to critical architecture decisions within a data driven environment. 

You’ll be part of a team that builds advanced software solutions for retail clients, focused on driving customer loyalty and personalization at scale. The team combines data, AI, and automation to help businesses better understand their customers and create meaningful, tailored experiences. By bringing together customer insights and strategy, the solutions enable retailers to design, manage, and optimize loyalty programs, customer journeys, and campaigns in real time—ensuring every interaction feels relevant and impactful.

With decades of expertise in retail and personalization, the team delivers a flexible, end-to-end platform that includes customer profile management, AI-driven predictions, campaign orchestration, and performance dashboards. Beyond implementation, the team works closely with clients to continuously refine strategies and maximize outcomes—helping businesses increase customer retention, influence behavior, and drive sustainable revenue growth in an increasingly AI-driven world.

Responsibilities:

• 3+ years of hands-on experience in Full Stack development, focusing on performance, scalability, security, and maintainability.  
• Strong proficiency in Frontend tech with expertise in any frontend framework.
• Strong proficiency in backend programming language, system design, Oops concepts.
• Drive code quality, ensuring adherence to best practices, design patterns, and SOLID principles.  
• Experience with cloud platforms (Google Cloud Platform & Azure), implementing cloud native best practices for scalability, security, and resilience.  
• Experience with containerization (Docker) and orchestration (Kubernetes, Helm).  
• Knowledge in CI/CD automation, with experience in GitOps workflows and Infrastructure-as Code (Terraform, Helm, or similar). 

About the Role:

We’re looking for a team player with excellent interpersonal skills & service oriented. Creative & out of the box thinker. An autodidact, quick, effective and versatile who’s able to change directions in midstream. Independent & Accountable.

What you’ll be spending your time on

• Create and maintain CI/CD pipelines for the company's products
• Building and maintaining high-performance, fault tolerant, scalable ALM system, from Version control, Builds and Deployments to Monitoring and configuration management
• Maintain the application layer of our public cloud and private cloud
• Develop and integrate infrastructure tools in support of our production system
• Automate the Provisioning and configuration of Windows/Linux environments
• Work closely with product, QA, developers and IT/operations departments to streamline their working methods
• As a core member of the team, you will participate in 'On-Call' duties on Payoneer production systems, working in non-conventional hours include weekends and holidays (from time to time)

Have you done this kind of stuff?

• BS degree in computer science, computer engineering, relevant technical discipline or equivalent practical experience
• At least 6 years’ experience as DevOps Engineer
• A minimum of 5 years of exposure running production workloads (AWS, Azure or GCP)
• Microservices architecture & container orchestration (Docker and Kubernetes)
• Experience with CI/CD tools and source control management tools (e.g., Git, Azure DevOps, SonarQube, Artifactory etc...)
• Experience with GitOps (e.g., ArgoCD or Flux)
• Experience with Configuration Managements tools like Chef, Ansible or Puppet
• Proven Scripting capabilities: PowerShell/Bash/Python
• High level Linux OS expertise
• Programming experience skills (C#, NodeJS - advantage)
• Experience managing application servers and web servers
• Strong troubleshooting skills
• Experience with monitoring and logging solutions (e.g. Prometheus, Grafana and ELK)
• Proactive by nature; internal drive for excellence and improvement

Not a must but a great advantage

• Experience in SQL
• Experience with software development and development frameworks
• Experience with event streaming and messaging platforms such as Kafka, RabbitMQ…
• Provisioning and operating NoSQL databases such as MongoDB, Redis, Elasticsearch …
• Knowledge and understanding Storage and Networking

#LI-PG1

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.

Role Summary

We are looking for a technically strong AI / ML Developer with hands-on expertise in training and fine-tuning Small Language Models (SLMs) and RAG Solutions. The ideal candidate will drive end-to-end AI Solutions — from dataset curation and pre-processing to training, evaluation, and production deployment. You will collaborate closely with product, product engineers, and infrastructure teams to build AI solutions that are efficient, scalable, and business-aligned.

Key Responsibilities

1  Model Design & Training

• Design, train, and fine-tune Small Language Models (SLMs) using frameworks such as PyTorch, TensorFlow, or JAX.
• Conduct experiments with supervised fine-tuning (SFT), reinforcement learning from human feedback (RLHF), and instruction tuning.
• Implement efficient training pipelines leveraging distributed training (DDP, FSDP) across GPU/TPU clusters.
• Perform hyperparameter optimisation, ablation studies, and model selection based on benchmark results.
• Develop and maintain data pipelines for collecting, cleaning, tokenising, and pre-processing large-scale training corpora.

2  Model Evaluation & Quality

• Define and implement evaluation frameworks including perplexity, BLEU, ROUGE, BERTScore, and task-specific benchmarks.
• Conduct red-teaming, bias analysis, and safety evaluations to ensure responsible AI deployment.
• Benchmark models against established baselines (e.g., GPT-2, Phi, Mistral) and track performance over iterations.
• Collaborate with QA teams to build regression suites for model versioning and continuous evaluation.

3  MLOps & Deployment

• Containerise and deploy models using Docker, Kubernetes, and cloud-native ML platforms (AWS SageMaker / GCP Vertex AI / Azure ML).
• Build and maintain model registries, experiment tracking (MLflow, Comet), and reproducible training pipelines.
• Optimise inference performance through quantisation (INT8, INT4), pruning, distillation, and ONNX/TensorRT conversion.
• Monitor model drift, data drift, and performance degradation in production; implement automated retraining triggers.

4  Research & Innovation

• Stay current with state-of-the-art NLP/LLM research; prototype and validate new techniques from published literature.
• Contribute to internal knowledge sharing, technical documentation, and model cards.
• Explore parameter-efficient fine-tuning (PEFT) methods such as LoRA, QLoRA, and Adapter layers.
• Investigate and apply mixture-of-experts (MoE), retrieval-augmented generation (RAG), and agentic workflows as needed.

5  Collaboration & Stakeholder Management

• Work with product managers and domain experts to translate business requirements into model objectives and KPIs.
• Communicate model capabilities, limitations, and trade-offs clearly to both technical and non-technical stakeholders.
• Participate in architecture reviews, sprint planning, and cross-functional design discussions.

Required Qualifications

1  Education

• Bachelor's or Master's degree in Computer Science, Data Science, Machine Learning, Statistics, or a related quantitative field.
• Equivalent professional experience with a strong portfolio of delivered AI/ML projects will be considered.

2  Experience

• 4 – 6 years of professional experience in machine learning or NLP engineering.
• Minimum 2 years of direct, hands-on experience in training or fine-tuning language models (LLMs or SLMs).
• Demonstrable experience taking a model from dataset preparation through to production deployment.

3  Technical Skills — Core

• Programming: Python (proficient); familiarity with C++/CUDA a plus.
• Deep Learning Frameworks: PyTorch (primary), TensorFlow or JAX.
• NLP Libraries: Hugging Face Transformers, Datasets, PEFT, TRL, Accelerate.
• Training Infrastructure: Multi-GPU training, FSDP, DeepSpeed ZeRO stages 1–3.
• Data Engineering: Pandas, NumPy, Apache Spark or Dask for large-scale data prep.
• Vector DBs & Retrieval: FAISS, Pinecone, Weaviate, or equivalent.
• Cloud Platforms: AWS, GCP, or Azure — ML-specific services (SageMaker, Vertex AI, etc.).
• Version Control & CI/CD: Git, GitHub/GitLab, MLflow or W&B for experiment tracking.

4  Technical Skills — Nice to Have

• Experience with multimodal models or vision-language models (VLMs).
• Knowledge of model safety, alignment techniques, and responsible AI frameworks.
• Familiarity with LangChain, LlamaIndex, or similar orchestration frameworks.
• Contributions to open-source ML projects or publications at NeurIPS, ICML, EMNLP, ACL.

Behavioural Competencies

• Intellectual Curiosity: Keeps up with rapidly evolving AI research and applies learnings pragmatically.
• Problem Solving: Approaches ambiguous problems with structured, data-driven thinking.
• Ownership: Takes full accountability for model quality, timelines, and production reliability.
• Collaboration: Works effectively in cross-functional teams with diverse skill sets.
• Communication: Distils complex technical concepts for diverse audiences.
• Adaptability: Thrives in a fast-paced environment where priorities evolve with research breakthroughs.

We’re looking for a Sr Full Stack Software Engineer who expects more from their career. This role offers an opportunity to build scalable, high-performance solutions in the engineering team, enhance code quality and engineering excellence, and contribute to critical architecture decisions within a data driven environment. 

You’ll be part of a team that builds advanced software solutions for retail clients, focused on driving customer loyalty and personalization at scale. The team combines data, AI, and automation to help businesses better understand their customers and create meaningful, tailored experiences. By bringing together customer insights and strategy, the solutions enable retailers to design, manage, and optimize loyalty programs, customer journeys, and campaigns in real time—ensuring every interaction feels relevant and impactful.

With decades of expertise in retail and personalization, the team delivers a flexible, end-to-end platform that includes customer profile management, AI-driven predictions, campaign orchestration, and performance dashboards. Beyond implementation, the team works closely with clients to continuously refine strategies and maximize outcomes—helping businesses increase customer retention, influence behavior, and drive sustainable revenue growth in an increasingly AI-driven world.

Responsibilities:

• 6+ years of hands-on experience in Full Stack development, focusing on performance, scalability, security, and maintainability.  
• Strong proficiency in Frontend tech with expertise in any frontend framework.
• Strong proficiency in backend programming language, system design, Oops concepts.
• Drive code quality, ensuring adherence to best practices, design patterns, and SOLID principles.  
• Experience with cloud platforms (Google Cloud Platform & Azure), implementing cloud native best practices for scalability, security, and resilience.  
• Hands On Experience with containerization (Docker) and orchestration (Kubernetes, Helm).  
• Experience in CI/CD automation, with experience in GitOps workflows and Infrastructure-as Code (Terraform, Helm, or similar). 

The mission of Speechify is to make sure that reading is never a barrier to learning.

Over 50 million people use Speechify’s text-to-speech products to turn whatever they’re reading – PDFs, books, Google Docs, news articles, websites – into audio, so they can read faster, read more, and remember more. Speechify’s text-to-speech reading products include its iOS app, Android App, Mac App, Chrome Extension, and Web App. Google recently named Speechify the Chrome Extension of the Year and Apple named Speechify its 2025 Design Award winner for Inclusivity.  

Today, nearly 200 people around the globe work on Speechify in a 100% distributed setting – Speechify has no office. These include frontend and backend engineers, AI research scientists, and others from Amazon, Microsoft, and Google, leading PhD programs like Stanford, high growth startups like Stripe, Vercel, Bolt, and many founders of their own companies.

Overview

We're looking to hire for our Data side of our AI team at Speechify. This role is responsible for all aspects of data collection to support our model training operations. We are able to build high-quality datasets at petabyte-scale and low cost through a tight integration of infrastructure, engineering, and research work. We are looking for a skilled Software Engineer to join us.

What You’ll Do

• Be scrappy to find new sources of audio data and bring it into our ingestion pipeline
• Operate and extend the cloud infrastructure for our ingestion pipeline, currently running on GCP and managed with Terraform.
• Collaborate closely with our Scientists to shift the cost/throughput/quality frontier, delivering richer data at bigger scale and lower cost to power our next-generation models.
• Collaborate with others on the AI Team and Speechify Leadership to craft the AI Team’s dataset roadmap to power Speechify’s next-generation consumer and enterprise products.

An Ideal Candidate Should Have

• BS/MS/PhD in Computer Science or a related field.
• 5+ years of industry experience in software development.
• Proficiency with bash/Python scripting in Linux environments
• Proficiency in Docker and Infrastructure-as-Code concepts and professional experience with at least one major Cloud Provider (we use GCP)
• Experience with web crawlers, large-scale data processing workflows is a plus
• Ability to handle multiple tasks and adapt to changing priorities.
• Strong communication skills, both written and verbal.

What we offer

• A fast-growing environment where you can help shape the company and product.
• An entrepreneurial-minded team that supports risk, intuition, and hustle.
• A hands-off management approach so you can focus and do your best work.
• An opportunity to make a big impact in a transformative industry.
• Competitive salaries, a friendly and laid-back atmosphere, and a commitment to building a great asynchronous culture.
• Opportunity to work on a life-changing product that millions of people use.
• Build products that directly impact and support people with learning differences like dyslexia, ADD, low vision, concussions, autism, and more.
• Work in one of the fastest-growing sectors of tech, the intersection of artificial intelligence and audio.

Think you’re a good fit for this job? 

Tell us more about yourself and why you're interested in the role when you apply.
And don’t forget to include links to your portfolio and LinkedIn.

Not looking but know someone who would make a great fit? 

Refer them! 

Speechify is committed to a diverse and inclusive workplace. 

Speechify does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.

Tesco Media is transforming how advertisers connect with consumers through personalized and targeted campaigns across retailers' digital and physical touchpoints. 
Retail Media Measurement plays a pivotal role in ensuring the effectiveness of these campaigns, driving value for advertisers, retailers, and consumers alike

Our mission: to enable businesses to grow and reimagine themselves by becoming advocates and champions for their customers. With deep heritage and expertise in retail – one of the world’s most competitive markets, with a deluge of multi-dimensional data – dunnhumby today enables businesses all over the world, across industries, to be Customer First.

Dunnhumby helps retailers and brands deliver better experiences through Customer First strategies.

We’re looking for a Full Stack Engineer who expects more from their career. This role offers an opportunity to build scalable, high-performance solutions in the engineering team, enhance code quality and engineering excellence, and contribute to critical architecture decisions within a data-driven environment. 

Responsibilities:

3+ years of hands-on experience in Full Stack development, focusing on performance, scalability, security, and maintainability.
Must have C# hands on experience + PHP hands on is highly desired
Strong proficiency in Frontend tech like React.js/Angular and Javascript.  
Strong proficiency in backend programming language, system design, OOP concepts.
Drive code quality, ensuring adherence to best practices, design patterns, and SOLID principle
Experience with cloud platforms (Google Cloud Platform & Azure), implementing cloud native best practices for scalability, security, and resilience.  
Good to have experience with containerization like Docker
Good to have knowledge in CI/CD automation.



Tesco Media operates at the heart of Tesco, powered by dunnhumby’s data and analytics expertise. While many roles are embedded day‑to‑day in the Tesco and Tesco Media environment, colleagues work across a unique partnership, collaborating closely with Tesco teams, Tesco Media stakeholders and dunnhumby specialists. Success in Tesco Media comes from building strong relationships across all three, bringing together retail scale, media capability and data‑led insight to deliver meaningful outcomes for customers and brands.

The mission of Speechify is to make sure that reading is never a barrier to learning.

Over 50 million people use Speechify’s text-to-speech products to turn whatever they’re reading – PDFs, books, Google Docs, news articles, websites – into audio, so they can read faster, read more, and remember more. Speechify’s text-to-speech reading products include its iOS app, Android App, Mac App, Chrome Extension, and Web App. Google recently named Speechify the Chrome Extension of the Year and Apple named Speechify its 2025 Design Award winner for Inclusivity.  

Today, nearly 200 people around the globe work on Speechify in a 100% distributed setting – Speechify has no office. These include frontend and backend engineers, AI research scientists, and others from Amazon, Microsoft, and Google, leading PhD programs like Stanford, high growth startups like Stripe, Vercel, Bolt, and many founders of their own companies.

Overview

The responsibilities of our Platform team include building and maintaining all backend services, including, but not limited to, payments, analytics, subscriptions, new products, text to speech, and external APIs.

This is a key role and ideal for someone who thinks strategically, enjoys fast-paced environments, is passionate about making product decisions, and has experience building great user experiences that delight users.

We are a flat organization that allows anyone to become a leader by showing excellent technical skills and delivering results consistently and fast. Work ethic, solid communication skills, and obsession with winning are paramount. 

Our interview process involves several technical interviews and we aim to complete them within 1 week. 

What You’ll Do

• Design, develop, and maintain robust APIs including public TTS API, internal APIs like Payment, Subscription, Auth and Consumption Tracking, ensuring they meet business and scalability requirements
• Oversee the full backend API landscape, enhancing and optimizing for performance and maintainability
• Collaborate on B2B solutions, focusing on customization and integration needs for enterprise clients
• Work closely with cross-functional teams to align backend architecture with overall product strategy and user experience

An Ideal Candidate Should Have

• Proven experience in backend development: TS/Node (required)
• Direct experience with GCP and knowledge of AWS, Azure, or other cloud providers
• Efficiency in ideation and implementation, prioritizing tasks based on urgency and impact
• Preferred: Experience with Docker and containerized deployments
• Preferred: Proficiency in deploying high availability applications on Kubernetes

What We Offer

• A dynamic environment where your contributions shape the company and its products
• A team that values innovation, intuition, and drive
• Autonomy, fostering focus and creativity
• The opportunity to have a significant impact in a revolutionary industry
• Competitive compensation, a welcoming atmosphere, and a commitment to an exceptional asynchronous work culture
• The privilege of working on a product that changes lives, particularly for those with learning differences like dyslexia, ADD, and more
• An active role at the intersection of artificial intelligence and audio – a rapidly evolving tech domain

Think you’re a good fit for this job? 

Tell us more about yourself and why you're interested in the role when you apply.
And don’t forget to include links to your portfolio and LinkedIn.

Not looking but know someone who would make a great fit? 

Refer them! 

Speechify is committed to a diverse and inclusive workplace. 

Speechify does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.

Retail Media is transforming how advertisers connect with consumers through personalized and targeted campaigns across retailers' digital and physical touchpoints.
Retail Media Measurement plays a pivotal role in ensuring the effectiveness of these campaigns, driving value for advertisers, retailers, and consumers alike

Our mission: to enable businesses to grow and reimagine themselves by becoming advocates and champions for their customers. With deep heritage and expertise in retail – one of the world’s most competitive markets, with a deluge of multi-dimensional data – dunnhumby today enables businesses all over the world, across industries, to be Customer First.

Dunnhumby helps retailers and brands deliver better experiences through Customer First strategies.

We are seeking a talented Lead Engineer with .NET expertise to lead development of a product that help Retailers transform their Retail Media business in a way that helps them achieve maximum ad revenue and enable massive scale.

As a Lead Engineer, you will play a pivotal role in designing and delivering high-quality software solutions.

You will be responsible for contributing to system architecture and ensuring adherence to engineering best practices. Your technical expertise, leadership skills, and ability to drive results will be key to the success of our products.

What will you be doing?

You will design and deliver .NET Core solutions within microservices architecture, ensuring adherence to compliance, security, and quality standards. Implement best practices in coding, CI/CD, and DevOps while balancing delivery timelines with technical excellence. Conduct regular performance reviews, provide actionable feedback, and drive innovation through continuous improvement and process enhancements. Focus on improving developer productivity and coaching junior team members to achieve their full potential. You will collaborate with product managers and architects to define technical roadmaps.

What would you need to be successful in the role?

• Experience 9+years
• Proven experience leading technical teams and delivering complex projects.
• Strong understanding of object-oriented programming, data structures, and algorithms.
• Possess strong technical expertise in C#, .NET Core and experience building RESTful APIs with a deep understanding of design patterns, SOLID principles, system design, and engineering best practices.
• Strong experience designing distributed systems using microservices and event-driven architecture
• Familiar with microservices and event-driven architecture using tools like RabbitMQ , Google Pub/Sub and Kafka, as well as containerization technologies such as Docker and Kubernetes.
• Hands-on experience with:
  
  • Docker and Kubernetes (K8s)
  • Cloud platforms (GCP / Azure / AWS)
  • Relational databases (Postgres preferred) and analytical databases (BigQuery preferred)
  • Testing Framework (Xunit / NUnit/ Cypress)
  .

• Experienced in using DevOps tools like GitLab CI/CD and leveraging cloud platforms, particularly GCP or Azure, for scalable solutions.
• Additional knowledge of Redis, and Elasticsearch is an advantage
• Demonstrate a deep understanding of distributed systems, cloud-native applications, and Unix/Linux environments, alongside expertise in testing strategies, code quality, and secure coding tools like SonarQube and Checkmarx.
• Proficiency with version control systems like Git
• Adept at utilizing observability tools like New Relic to monitor systems, with solid knowledge of SDLC, Agile methodologies, and strong interpersonal and leadership skills to effectively motivate teams.
• Familiarity with the AdTech or Retail domain is an added advantage
• Work experience preferably in a product company

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.