Jobiba hiring network

Full Stack Software Engineer 2c Api Experience Jobs

4,379 active opportunities · Updated for October 2026

Fresh results

15 shown

Explore current full stack software engineer 2c api experience jobs. Use filters to narrow by work mode, employment type, experience and date posted.

CA
13 days ago

A BOUT TIDE At Tide, we help SMEs save time and money in the running of their businesses by not only offering business accounts and related banking services, but also a comprehensive set of highly usable and connected administrative solutions, from invoicing to accounting. Tide is transforming the small business banking market and now supports over 2 million members globally across the UK, India, Germany and France. Using advanced technology, all solutions are designed with SMEs in mind. With quick onboarding, low fees and innovative features, we thrive on making data driven decisions to serve our mission: to help SMEs save time and money so they can get back to doing what they love. Tide facts: Tide is available for UK, Indian, German and French SMEs Over 2 million members across UK and India Over $300 million raised in funding Over 2,800 Tideans globally Recognised with Great Place to Work certification three years in a row, and among India’s Top 50 Best Workplaces in Banking, Financial Services, and Insurance in 2026 We have offices in Central London, with a member support and technology centre in Sofia, Bulgaria, technology centres in Serbia, Romania, Lithuania and Hyderabad and offices in Gurugram, New Delhi, Berlin, Paris and Luxembourg About the role: As a Senior Product Analyst ( Member Acquisition Marketing ) , you’ll be responsible for managing insights projects related to member growth & acquisition. As a Product Analyst you’ll be: Presenting insights to stakeholders & senior management, translating analysis into the 'so what?' and identifying possible actions to take as a result Using your SQL/Python expertise to interrogate our data to solve key business problems Focusing on improving performance marketing and growth initiatives by providing full stack descriptive to prescriptive analytics via cutting edge technologies to support business objectives Ability to deal with ambiguity & form ambiguous questions into define

pythonsqlai
View job →
CA
13 days ago

A BOUT TIDE At Tide, we help SMEs save time and money in the running of their businesses by not only offering business accounts and related banking services, but also a comprehensive set of highly usable and connected administrative solutions, from invoicing to accounting. Tide is transforming the small business banking market and now supports over 2 million members globally across the UK, India, Germany and France. Using advanced technology, all solutions are designed with SMEs in mind. With quick onboarding, low fees and innovative features, we thrive on making data driven decisions to serve our mission: to help SMEs save time and money so they can get back to doing what they love. Tide facts: Tide is available for UK, Indian, German and French SMEs Over 2 million members across UK and India Over $300 million raised in funding Over 2,800 Tideans globally Recognised with Great Place to Work certification three years in a row, and among India’s Top 50 Best Workplaces in Banking, Financial Services, and Insurance in 2026 We have offices in Central London, with a member support and technology centre in Sofia, Bulgaria, technology centres in Serbia, Romania, Lithuania and Hyderabad and offices in Gurugram, New Delhi, Berlin, Paris and Luxembourg About the role: As a Senior Product Analyst ( Member Acquisition Marketing ) , you’ll be responsible for managing insights projects related to member growth & acquisition. As a Product Analyst you’ll be: Presenting insights to stakeholders & senior management, translating analysis into the 'so what?' and identifying possible actions to take as a result Using your SQL/Python expertise to interrogate our data to solve key business problems Focusing on improving performance marketing and growth initiatives by providing full stack descriptive to prescriptive analytics via cutting edge technologies to support business objectives Ability to deal with ambiguity & form ambiguous questions into define

pythonsqlai
View job →
H
1mo ago

Become a part of our caring community Most AI engineering jobs are a thin wrapper around a model API. This role is different. We build the platform that transforms millions of clinical documents into trusted, actionable data. Our systems use large language models (LLMs) to read medical records, extract structured facts, answer complex questions with citations back to the source document, and route ambiguous cases to human experts for review. Our users make decisions that impact real healthcare outcomes, so “good enough” is not good enough. Building AI systems that are accurate, reliable, auditable, and scalable is at the core of this role. As a Senior AI Applied Engineer, you will design, build, deploy, and operate production AI systems used at scale within one of the largest health insurers in the United States. You will own solutions end-to-end, from user experience and APIs to model orchestration, evaluation frameworks, infrastructure, and production operations. Why Join Us Build production AI systems where LLMs are in the critical path, not just demos or proofs of concept. Work on extraction, retrieval, agentic workflows, and human-review systems that process real healthcare data at scale. Own projects end-to-end across frontend, backend, AI orchestration, infrastructure, deployment, and operations. Solve challenging problems around accuracy, explainability, traceability, and reliability in regulated environments. Ship quickly in a small, high-impact team that embraces AI-assisted development and rigorous quality standards. Build systems that continuously improve through expert feedback, evaluations, and human-in-the-loop workflows. Key Responsibilities Design, develop, and deploy full-stack AI-powered application

javascripttypescriptpython
View job →
S
Stripe
📍 San Francisco• Full-time
16 days ago

About Stripe Stripe is a financial infrastructure platform for businesses. Millions of companies - from the world’s largest enterprises to the most ambitious startups - use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone's reach while doing the most important work of your career. About the team The AI team is focused on one of Stripe’s most strategic growth areas: enabling the monetization and scaling of AI-native and AI-enabled businesses. We’re in a unique position – partnering with the world’s most ambitious AI companies (the likes of OpenAI, Anthropic, NVIDIA, etc) building on the frontier of artificial intelligence -- across infrastructure, foundation models, agents, and applications -- to help them grow and commercialize globally using Stripe’s full financial stack. As part of Stripe’s GTM / Sales organization, this team works closely with Product, Engineering, and Marketing to shape Stripe’s AI GTM strategy and ensure that the world’s leading AI companies -- from early-stage innovators to the largest public players -- choose Stripe as their monetization platform. What you’ll do Work with existing Stripe customers in the AI Industry to develop and execute long-term sales strategies to expand Stripe’s revenue Own the full sales cycle, from business case development, to deal structuring and negotiating, to close Develop account plans and cross sell into your list of strategic AI customers, driving growth through expansion and new revenue streams Drive deal strategy and commercial negotiations for large, complex renewals Develop relationships with executive stakeholders within your book of business, deeply understanding problems they are solving and helping drive to solutions Be responsible for account mapping and coordinating ef

restaigo
View job →
O
1mo ago

About the Team The Health team, within OpenAI’s broader Personal AGI organization, has a mission to ensure AGI improves health for all humanity. Improving human health will be one of the defining impacts of AGI. Hundreds of millions of people already turn to ChatGPT for questions about their health and millions of clinicians use it weekly to support care delivery. Increasingly capable models create an opportunity to make high-quality medical intelligence more accessible across patients and clinicians—raising the floor of human health—and accelerate the new capabilities and scientific advances that raise the ceiling of human health. Our job is to make those benefits real. We work across the full model stack—pretraining, midtraining, reinforcement learning, post-training, evaluations, harnessing, and deployment—and connect that research to the patients, clinicians, and real-world outcomes we aim to improve. About the Role We’re looking for an exceptional, hands-on researcher who wants to build frontier health capabilities and turn them into impact at scale. This is a role for someone who can take an important, underdefined problem from 0→1: identify the right bet, build what’s needed to test it, and drive it all the way to a measurable improvement in the models and products we actually ship. We’re especially excited about two kinds of people: researchers with the technical depth to move the frontier in pretraining, reinforcement learning (RL) / post-training, or evals; and researchers with real depth in developing frontier biomedical AI capabilities. Prior experience in healthcare is helpful but not required. Research excellence, velocity, ownership, and alignment with the mission are most important to us. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: Own a high-leverage research direction end to end—from deciding which problem matters and h

machine learningartificial intelligenceai
View job →

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. We are looking for talented systems developers and researchers to join the Snowflake AI Research team and advance the state of the art in LLM inference systems and optimization . Our mission is to build the next generation of high-performance and intelligent inference systems . We optimize not only how fast and efficiently models run, but also how quickly inference systems can adapt to new models, architectures, hardware, and workloads. Our work spans the full inference stack—from distributed serving and runtime systems to GPU kernels and model-system co-design. We explore techniques such as adaptive parallelism, speculative and parallel decoding, disaggregated inference, scheduling and batching, KV-cache optimization, model swapping, quantization, and GPU kernel optimization to push the frontier of latency, throughput, scalability, and cost. Beyond optimizing individual models, we are building intelligent and adaptive inference systems that can automate performance optimization—rapidly profiling new models and workloads, identifying bottlenecks, selecting effective execution strategies, and adapting system configurations with minimal manual tuning. We embrace AI-native engineering , using AI not only as the workload we optimize, but also as a tool to accelerate system deve

machine learningaiswift
View job →
N
13 days ago

NVIDIA is at the forefront of the AI and robotics revolution, and NVIDIA’s robotics teams are on a mission to build the essential technology that can enable any company to become a robotics company. The Seattle Robotics Lab is uniquely positioned at the intersection of open academic research and real-world industry impact, pursuing fundamental and applied robotics research across the full robotics stack, including perception, planning, control, reinforcement learning, imitation learning, simulation, and robotics foundation models. This research aims to transform research paradigms, transfer into NVIDIA’s robotics and simulation products, and create new robotics markets for the world. The Seattle Robotics Lab has published over 500 research papers, including many influential works that have been presented at top robotics, AI, and computer vision conferences. These works include BayesSim , cuRobo , DeXtreme , DiSECT , Factory , GraspNet , IndustReal , ITPS , LAPA , <a href="h

pythonmachine learningai
View job →

About the Role Adobe is seeking a Machine Learning Engineer to join the Adobe Genuine Engineering team. This group protects Adobe's ecosystem from fraud, abuse, and misuse using intelligent systems worldwide. In this position, you will build and develop machine learning models from scratch, including custom transformer-based frameworks, to identify fraudulent actions, stop account sharing, and protect the experience of hundreds of millions of users. You will manage the entire model lifecycle: raw behavioral data and feature engineering, architecture development, large-scale GPU training, deployment, and monitoring. The team is actively building in-house behavioral foundation models that learn identity-preserving representations from long sequences of user activity. This is a role for an engineer who wants to own deep learning systems end-to-end — not consume pre-built ones. Key Responsibilities Build and train deep learning models from scratch, including custom transformer and attention-based architectures for long behavioral event sequences. Own the full training stack: event tokenization, temporal and positional embeddings, self-supervised pretraining (e.g., masked modeling, contrastive learning), and downstream fine-tuning. Train large models efficiently on GPU infrastructure using mixed-precision training, gradient accumulation/checkpointing, efficient attention, and distributed strategies (DDP, FSDP, or equivalent). Build and optimize feature pipelines on Databricks and Spark, transforming raw behavioral events into high-quality model inputs. Translate prototypes into production ML systems — scalable, reliable, and observable — and drive inference performance through architectural and serving-side optimization. Contribute to MLOps practices: experiment tracking, model versioning, CI/CD, automated retraining, and

pythonmachine learningai
View job →
A
1mo ago

About the Role Adobe is seeking a Machine Learning Engineer to join the Adobe Genuine Engineering team. This group protects Adobe's ecosystem from fraud, abuse, and misuse using intelligent systems worldwide. In this position, you will build and develop machine learning models from scratch, including custom transformer-based frameworks, to identify fraudulent actions, stop account sharing, and protect the experience of hundreds of millions of users. You will manage the entire model lifecycle: raw behavioral data and feature engineering, architecture development, large-scale GPU training, deployment, and monitoring. The team is actively building in-house behavioral foundation models that learn identity-preserving representations from long sequences of user activity. This is a role for an engineer who wants to own deep learning systems end-to-end — not consume pre-built ones. Key Responsibilities Build and train deep learning models from scratch, including custom transformer and attention-based architectures for long behavioral event sequences. Own the full training stack: event tokenization, temporal and positional embeddings, self-supervised pretraining (e.g., masked modeling, contrastive learning), and downstream fine-tuning. Train large models efficiently on GPU infrastructure using mixed-precision training, gradient accumulation/checkpointing, efficient attention, and distributed strategies (DDP, FSDP, or equivalent). Build and optimize feature pipelines on Databricks and Spark, transforming raw behavioral events into high-quality model inputs. Translate prototypes into production ML systems — scalable, reliable, and observable — and drive inference performance through architectural and serving-side optimization. Contribute to MLOps practices: experiment tracking, model versioning, CI/CD, automated retraining, and

pythonmachine learningai
View job →

About the Role Adobe is seeking a Machine Learning Engineer to join the Adobe Genuine Engineering team. This group protects Adobe's ecosystem from fraud, abuse, and misuse using intelligent systems worldwide. In this position, you will build and develop machine learning models from scratch, including custom transformer-based frameworks, to identify fraudulent actions, stop account sharing, and protect the experience of hundreds of millions of users. You will manage the entire model lifecycle: raw behavioral data and feature engineering, architecture development, large-scale GPU training, deployment, and monitoring. The team is actively building in-house behavioral foundation models that learn identity-preserving representations from long sequences of user activity. This is a role for an engineer who wants to own deep learning systems end-to-end — not consume pre-built ones. Key Responsibilities Build and train deep learning models from scratch, including custom transformer and attention-based architectures for long behavioral event sequences. Own the full training stack: event tokenization, temporal and positional embeddings, self-supervised pretraining (e.g., masked modeling, contrastive learning), and downstream fine-tuning. Train large models efficiently on GPU infrastructure using mixed-precision training, gradient accumulation/checkpointing, efficient attention, and distributed strategies (DDP, FSDP, or equivalent). Build and optimize feature pipelines on Databricks and Spark, transforming raw behavioral events into high-quality model inputs. Translate prototypes into production ML systems — scalable, reliable, and observable — and drive inference performance through architectural and serving-side optimization. Contribute to MLOps practices: experiment tracking, model versioning, CI/CD, automated retraining, and

pythonmachine learningai
View job →
S
1mo ago

Who we are About Stripe Stripe is a financial infrastructure platform for businesses. Millions of companies - from the world’s largest enterprises to the most ambitious startups - use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone's reach while doing the most important work of your career. About the team The AI team is focused on one of Stripe’s most strategic growth areas: enabling the monetization and scaling of AI-native and AI-enabled businesses. We’re in a unique position – partnering with the world’s most ambitious AI companies (the likes of OpenAI, Anthropic, NVIDIA, etc) building on the frontier of artificial intelligence -- across infrastructure, foundation models, agents, and applications -- to help them grow and commercialize globally using Stripe’s full financial stack. As part of Stripe’s GTM / Sales organization, this team works closely with Product, Engineering, and Marketing to shape Stripe’s AI GTM strategy and ensure that the world’s leading AI companies -- from early-stage innovators to the largest public players -- choose Stripe as their monetization platform. What you’ll do Work with existing Stripe customers in the AI Industry to develop and execute long-term sales strategies to expand Stripe’s revenue Own the full sales cycle, from business case development, to deal structuring and negotiating, to close Develop account plans and cross sell into your list of strategic AI customers, driving growth through expansion and new revenue streams Drive deal strategy and commercial negotiations for large, complex renewals Develop relationships with executive stakeholders within your book of business, deeply understanding problems they are solving and helping drive to solutions Be responsible for account mapping and coor

artificial intelligenceai
View job →
O
OpenAI
📍 San Francisco• Full-time
1mo ago

About the Team OpenAI’s acquisition of io marks our entry into consumer hardware and our ambition to define the next human–computer interface. Success in hardware requires strong financial stewardship across the full product cost stack—from early design and sourcing decisions through manufacturing, logistics, inventory, returns, and warranty. Hardware Finance works across Product, Supply Chain, Operations, Accounting, Systems/Data, and Finance to connect business decisions to product cost, inventory, cash, COGS, and margin. About the Role We are seeking a Hardware Finance Manager to own an assigned area of hardware COGS and inventory end to end. The initial assignment will depend on business priorities and the successful candidate’s expertise. It may include BOM and product cost, manufacturing variance analysis, inventory planning, logistics, returns and warranty, customer support, or another connected set of hardware-finance responsibilities. This is an individual-contributor role with broad scope. Prior hardware experience and deep, hands-on expertise in at least two relevant domains are required. The person will be expected to operate independently, build reusable processes and analytical workflows, and remain accountable for the analysis, judgment, and recommendations. In this role, you will: Own an assigned area of hardware COGS and inventory end to end. Own forecasting, close, and business variance analysis for the assigned scope. Provide hardware leadership with clear variance explanations, trend analysis, and forward-looking signals that connect business and supplier decisions to inventory, cash, COGS, and margin. Partner with business teams and Finance Platforms to establish the financial data, systems, and dashboards needed to support analysis. Ensure data integrity and governance through clear definitions, ownership, validation checks, controls, and review processes. Improve forecasting, reporting, systems, and finance processes so they remain reliable an

awsrestai
View job →
L
Lyft
📍 San Francisco• Full-time• From $1.8M/yr
1mo ago

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. The People Technology stack has never been more capable, the differentiator now is the expertise to unlock it. . As a Senior Workday Engineer at Lyft, you'll be the technical cornerstone of our People Technology team, owning the design, development, and delivery of the integrations, custom applications, and AI solutions that the entire People function depends on. This role uniquely combines deep, demonstrable mastery across the full Workday technology stack with an AI-native engineering approach, enabling you to build solutions that don't just automate what exists today but fundamentally raise the bar for how People Technology delivers value. We're seeking a hands-on engineer who commands the full depth of the Workday ecosystem, from Studio and Core Connectors to Extend and Prism Analytics, and brings the technical judgment to architect solutions that scale with the business. You'll be the trusted technical owner of our People Technology platforms, partnering closely with HR, Payroll, Finance, and Benefits stakeholders to translate complex requirements into scalable, maintainable solutions that truly move the needle. With AI reshaping how People Technology teams operate, your expertise will be critical in actively identifying, building, and shipping AI-powered solutions that eliminate manual work, accelerate delivery, and push our teams from tactical execution to strategic impact. In this role, you'll integrate LLMs into HR workflows, build and maintain MCP servers that expose People systems data securely to AI agents, mentor junior engineers, and set the engineering standard for a team that is redefining what enterprise People Technology looks like. If you are a candidate who has the vision of what could be, who has the ability to cultivate relationships, and has a belief in driving impact, then you

restaigo
View job →
C-
CLEAR - Corporate
📍 New York• Full-time• $225K – $275K/yr
16 days ago

CLEAR is building THE secure identity company of the future. Our mission is to make experiences safer and easier—physically and digitally. With more than 43 million Members and a growing network of partners across the world, CLEAR's secure identity platform is transforming the way people live, work, and travel. Whether it’s at the airport, stadium, or throughout your everyday life, CLEAR unlocks the magic of frictionless experiences. We’re looking for a strategic and execution-oriented Senior Director, Revenue Operations to lead and scale the operational backbone of our B2B organization. Sitting within B2B Operations, this role will own the strategy, architecture, and optimization of our revenue systems, processes, and analytics across Sales, Customer Success, and Marketing. You will serve as a key partner to B2B leadership, driving operational rigor, scalable infrastructure, and data-driven decision-making to accelerate revenue growth. You will define the roadmap for revenue systems, lead cross-functional initiatives, and build the foundation for long-term scale. What you'll do: Define and execute the B2B Revenue Operations roadmap in alignment with C1 growth objectives Act as a strategic partner to B2B leadership on forecasting, pipeline health, performance metrics, and operational investments. Establish scalable processes that improve conversion, velocity, forecasting accuracy, and revenue predictability at scale. Lead the redesign of Salesforce to support complex B2B sales motions, with hands-on responsibility for system configuration, reports, and dashboards Architect and optimize the full revenue tech stack (Salesforce, Outreach, ZoomInfo, HubSpot, Gong, LinkedIn Sales Navigator, etc.) Maintain data quality (deduplication, enrichment, normalization), build and evolve reporting frameworks, and troubleshoot integration issues across the revenue tech stack when they arise. Create and maintain internal documentation, runbooks, and training materials; support enabl

gitrestai
View job →
S
1mo ago

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. LEAD. STRATEGIZE. TRANSFORM. We are seeking an advanced professional handling complex enterprise AI/ML deployments, deconstructing system dependencies, and ensuring production robustness. WHY THIS ROLE? This role marks a shift from managing tactical tasks to managing strategic outcomes. You are a seasoned professional with a full understanding of your specialization, resolving a wide range of issues in creative ways. WHAT YOU'LL DO: Design robust, scalable AI/ML solutions utilizing the full Snowflake native stack and partner ecosystem. Perform deep-dive Root Cause Analysis (RCA) for complex system dependencies in AI/ML solutions. Collaborate cross-functionally with Sales and Product teams to align technical roadmaps with customer ROI. Mentor Level 3 architects on best practices for MLOps and architectural design. TECHNICAL DEPTH & RISK MANAGEMENT: Distributed Systems: Deconstruct failures in complex pipelines involving external cloud services (AWS/Azure/GCP). Predictive Failure Analysis: Critically think about potential failure modes like model drift and data skew early in the lifecycle. Governance: Architect data security and access controls specifically for sensitive AI/ML training data. SNOWFLAKE-NATIVE TECH STACK: Snowflake Model Registry, Cortex Functions, Python,

pythonawsazure
View job →
🔔

Get new full stack software engineer 2c api experience jobs by email

Daily job updates · Unsubscribe anytime