Engineering Journal Jobs in San Carlos, CA

About Pinterest:

Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we're on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product.

Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other's unique experiences and embrace theflexibility to do your best work. Creating a career you love? It's Possible.

At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we're looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we'll explore your foundational skills and how you collaborate with AI.

Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here.

With more than 500 million users around the world and 300 billion ideas saved, Pinterest Machine Learning engineers build personalized experiences to help Pinners create a life they love. With just over 4,000 global employees, our teams are small, mighty, and still growing. At Pinterest, you'll experience hands-on access to an incredible vault of data and contribute large-scale recommendation systems in ways you won't find anywhere else.

Within the Monetization ML Engineering team, we try to connect the dots between the aspirations of Pinners and the products offered by our partners. In this role, you will be responsible for developing and executing a vision for the evolution of the machine learning technology stack within Ads.

What you'll do:

• 
  
• Build cutting edge technology using the latest advances in deep learning and machine learning to personalize Pinterest
  
• Partner closely with teams across Pinterest to experiment and improve ML models for various product surfaces (Homefeed, Ads, Growth, Shopping, and Search), while gaining knowledge of how ML works in different areas
  
• Use data driven methods and leverage the unique properties of our data to improve candidates retrieval
  
• Work in a high-impact environment with quick experimentation and product launches
  
• Keep up with industry trends in recommendation systems
  
• Leverage LLMs to enhance content understanding
  

What we're looking for:

• 
  
• 2+ years of industry experience applying machine learning methods (e.g., user modeling, personalization, recommender systems, search, ranking, natural language processing, reinforcement learning, and graph representation learning)
  
• Degree in computer science, statistics, or related field; or equivalent experience
  
• End-to-end hands-on experience with building data processing pipelines, large scale machine learning systems, and big data technologies (e.g., Hadoop/Spark)
  
• Practical knowledge of large scale recommender systems, or modern ads ranking, retrieval, targeting, marketplace systems
  
• Nice to have:
  
  • 
    
  • M.S. or PhD in Machine Learning or related areas
    
  • Publications at top ML conferences
    
  • Expertise in scalable realtime systems that process stream data
    
  • Passion for applied ML and the Pinterest product
    
  • Background in computational advertising
    
  
  
  

Relocation Statement:

• 
  
• This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model.
  

#LI-HYBRID

At Pinterest we believe the workplace should be equitable, inclusive, and inspiring for every employee. In an effort to provide greater transparency, we are sharing the base salary range for this position. The position is also eligible for equity. Final salary is based on a number of factors including location, travel, relevant prior experience, or particular skills and expertise.

Information regarding the culture at Pinterest and benefits available for this position can be found here.

Our Commitment to Inclusion:

About Pinterest:

Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we're on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product.

Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other's unique experiences and embrace theflexibility to do your best work. Creating a career you love? It's Possible.

At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we're looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we'll explore your foundational skills and how you collaborate with AI.

Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here.

With more than 600 million users around the world and 300 billion ideas saved, Pinterest Machine Learning engineers build personalized experiences to help Pinners create a life they love. With just over 4,000 global employees, our teams are small, mighty, and still growing. At Pinterest, you'll experience hands-on access to an incredible vault of data and contribute large-scale recommendation systems in ways you won't find anywhere else.

Within the Monetization ML Engineering team, we try to connect the dots between the aspirations of Pinners and the products offered by our partners. In this role, you will be responsible for developing and executing a vision for the evolution of the machine learning technology stack within Ads.

What you'll do:

• 
  
• Build cutting edge technology using the latest advances in deep learning and machine learning to personalize Pinterest
  
• Partner closely with teams across Pinterest to experiment and improve ML models for various product surfaces (Homefeed, Ads, Growth, Shopping, and Search), while gaining knowledge of how ML works in different areas
  
• Use data driven methods and leverage the unique properties of our data to improve candidates retrieval
  
• Work in a high-impact environment with quick experimentation and product launches
  
• Keep up with industry trends in recommendation systems
  
• Leverage LLMs to enhance content understanding
  

What we're looking for:

• 
  
• 2+ years of industry experience applying machine learning methods (e.g., user modeling, personalization, recommender systems, search, ranking, natural language processing, reinforcement learning, and graph representation learning)
  
• Degree in computer science, machine learning, statistics, or related field
  
• End-to-end hands-on experience with building data processing pipelines, large scale machine learning systems, and big data technologies (e.g., Hadoop/Spark)
  
• Practical knowledge of large scale recommender systems, or modern ads ranking, retrieval, targeting, marketplace systems
  
• Nice to have:
  
  
  • 
    
  • Publications at top ML conferences
    
  • Expertise in scalable realtime systems that process stream data
    
  • Passion for applied ML and the Pinterest product
    
  • Background in computational advertising
    
  
  
  

Relocation Statement:

• 
  
• This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model.
  

#LI-HYBRID

#LI-SM4

At Pinterest we believe the workplace should be equitable, inclusive, and inspiring for every employee. In an effort to provide greater transparency, we are sharing the base salary range for this position. The position is also eligible for equity. Final salary is based on a number of factors including location, travel, relevant prior experience, or particular skills and expertise.

Information regarding the culture at Pinterest and benefits available for this position can be found here.

Our Commitment to Inclusion:

Fractal is a strategic AI partner to Fortune 500 companies, with a bold vision: to power every human decision in the enterprise. We believe the future belongs to organizations that combine human imagination with intelligent systems—and Fractalites are the ones building that future. As we scale our Technology, Media & Telecom (TMT) practice in the United States, we are looking for a senior, client-facing Head of Engineering to shape and deliver world-class Data & AI platforms for leading Technology, Media & Telecom organizations.

This is not a back-office engineering role. This is a consulting-led, client-facing engineering leadership position for someone who is equally comfortable whiteboarding architecture with principal engineers, rolling up their sleeves with delivery teams, and advising CIOs, CTOs, and CDOs in the boardroom.

Learn more at Fractal | Intelligence for Imagination.

Note: This position is not eligible for Immigration Sponsorship at this time.

About the Role

This is a four-axis leadership role requiring technical depth, executive presence, team leadership, and embedded delivery. You'll work directly with top technical and functional leaders at some of the largest TMT companies in the world.

As Head of Engineering for Fractal's Technology, Media & Telecom (TMT) vertical, you will personally shape the architecture of mission-critical AIML platforms, often in first-party tech stack, and develop/drive the team of ICs who bring them to life.

Responsibilities

Some engagements will look like a traditional advisory model. Others will look a lot more like Forward Deployed Engineering: your team embedded inside a client's engineering org, working within their first-party tech stack, shipping production code alongside their engineers, and earning influence through technical credibility, not org chart position.

You will need to be in the room when the technology roadmap needs to change. When a business pivot, a new regulation, or a technology shift forces a rethink mid-execution, you are the person who picks up the marker, walks to the whiteboard, and redraws the architecture in real time, credibly, for the CTO, and Principal Engineering leaders simultaneously.

Technical Depth (Hands-On Architecture)

• Own AI/Data platform architecture decisions — from Lakehouse design and real-time streaming to MLOps, LLMOps, and AgentOps pipelines in production
• Serve as the technical authority for Fractal's TMT engineering practice — defining standards, reviewing design, and holding the bar on reliability, scalability, and security
• Translate ambiguous business problems into concrete, buildable platform architectures — and stay close enough to execution to know when something is not working
• Drive the industrialization of GenAI: moving clients from proof-of-concept to enterprise-grade, governed, and observable AI systems

Executive Presence & Live Architectural Thinking

• Command the room with senior client leadership — CIOs, CTOs, CDOs, and their direct reports - as a peer, not a vendor
• Whiteboard new architectural directions on the spot: when a business pivot, acquisition, regulatory shift, or technology breakthrough forces a mid-execution rethink, you synthesize it into a credible, buildable path forward live, in the room, without needing a week to prepare a deck
• Translate between two worlds simultaneously: make the architecture legible to a CFO and rigorous enough to satisfy a principal engineer in the same session
• Shape client roadmaps at the strategic level; identifying where the current plan is under-ambitious, over-engineered, or misaligned with emerging AI capabilities, and steering accordingly
• Represent Fractal at the highest level of client relationship

Team Leadership (Building & Driving Senior ICs)

• Develop and lead a high-performing group of individual contributors. principally senior and staff engineers, ML engineers, and data platform engineers
• Create the engineering culture: rigorous delivery standards, architectural thinking, and a bias toward elegant, production-grade solutions over quick fixes
• Build leadership depth within the team, identifying principals who can own programs and grow into broader roles
• Partner across Fractal's global AI and engineering Capability functions to staff programs strategically and raise capability across the TMT practice

Forward-Deployed & Embedded Delivery

• Lead and run FDE-style engagements where your team operates inside the client's engineering environment
• Navigate and deliver within client-owned, first-party technology stacks: proprietary data platforms, internal ML infrastructure, custom orchestration systems, and bespoke toolchains that do not appear in any industry survey
• Adapt quickly to non-standard environments, understanding a client's internal platform deeply enough to extend it, integrate into it, and earn the trust of their engineering staff
• Balance the tension between what Fractal does best and what the client's stack demands, knowing when to bring pattern, when to adapt, and when to advocate for a better path
• Set the standards for how Fractal operates in deeply embedded engagements: how we onboard, document, transfer knowledge, and leave clients stronger than we found them

Candidate Profile

Technical Qualifications

TMT clients bring genuinely hard problems on both open and proprietary infrastructure. Expect to architect and oversee:

• GenAI systems: RAG architectures, LLM fine-tuning pipelines, agentic workflow orchestration, and LLMOps observability
• AI-powered products: personalization engines, churn prediction, content recommendation, and network fault detection
• Client-proprietary ML infrastructure: internal feature stores, custom model serving layers, bespoke experiment tracking systems, and first-party orchestration frameworks
• Cloud-native infrastructure across AWS, Azure, and GCP with enterprise-grade governance, security, and compliance baked in
• Real-time and event driven data pipelines (e.g. network telemetry)
• Modern Lakehouse platforms (Databricks, Snowflake, Delta Lake, Iceberg) at petabyte scale and proprietary data platform equivalents at leading tech-forward TMT organizations

Non-technical Qualifications

We are particularly interested in leaders from environments where engineering rigor, client accountability, executive presence, and AI depth all coexist including Forward Deployed Engineering, elite data/ML platform teams, and senior hyperscaler architecture practices.

• 15–20 years of experience spanning AI/data engineering and technical leadership with clear evidence of owning architecture at scale
• Deep hands-on experience deploying AI/ML/GenAI systems in production, in addition to advising on them
• Demonstrated executive presence: you have walked into a CTO or CDO review, redrawn the architecture based on new constraints, and left the room with alignment
• The ability to whiteboard fluently under pressure, synthesizing a team's in-flight work with a new business direction, making it rigorous enough for engineers and clear enough for executives, on the spot and without a rehearsal
• Experience operating within client-owned or non-standard technology stacks - you have learned a proprietary system, earned trust from skeptical internal engineers, and delivered production-grade results inside someone else's infrastructure
• A track record of leading senior engineers and building high-performance ML/engineering teams, including hiring, coaching, and developing principal-level ICs
• Direct executive engagement experience - you have influenced CIO/CTO/CDO decisions and can hold your own in a room with technical and non-technical stakeholders at once
• Strong cloud-native fluency across one or more hyperscalers, with genuine depth in data platform patterns (streaming, batch, Lakehouse, governance)

Strong Preferences

• Experience in TMT vertical — hi-tech, telco, media platforms, streaming infrastructure, ad tech, or content delivery at scale
• Prior work in FDE-style or embedded delivery models where your team shipped inside a client codebase and was evaluated by their engineering standards, not just deliverable milestones
• Comfort with the ambiguity of 1P stack environments: you have debugged undocumented internal tools, extended proprietary frameworks, and figured out how to make external expertise land inside a closed ecosystem
• A personal reputation for architectural clarity: the person colleagues call when a problem needs to be drawn, not just describe
• Contributions to the ML/AI community: open source, publications, conference talks, or influential architectural patterns

Who Thrives Here

The Fractalite mindset is curious, rigorous, and impact driven. You will thrive in this role if you:

• Enjoy being client-facing and accountable for outcomes.
• Are comfortable navigating ambiguity, scale, and complex stakeholder environments.
• Believe great platforms come from strong engineering culture plus disciplined execution.
• See AI not as a novelty, but as a core enterprise capability that must be engineered responsibly.

Fractal provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.

Talent Acquisition Manager – AI Infrastructure & Engineering

San Francisco, California

Hybrid Working

We are expanding our global team and launching a new office in San Francisco.

WNTD is looking for an experienced Talent Acquisition Manager to join our Talent Solutions team and support the continued growth of AI infrastructure and accelerated compute platforms across North America.

This role will support one of the most significant AI infrastructure expansion programmes currently underway, focused on building next generation platforms powered by NVIDIA accelerated compute.

You will work closely with senior technical leaders to attract and hire talent across the full infrastructure stack including software engineering, AI platforms, GPU environments and large scale compute infrastructure.

This is a delivery focused role supporting high growth engineering programmes across AI infrastructure and cloud platforms.

The Role

You will lead hiring across multiple engineering disciplines spanning software engineering, AI infrastructure platforms and high performance compute environments.

Working closely with technical leadership and programme stakeholders, you will build pipelines of high quality candidates and manage fast moving hiring plans across several technical workstreams.

Key Responsibilities

• Build and manage talent pipelines across software engineering, AI infrastructure and GPU compute environments

• Proactively source talent across the United States through mapping, referrals and direct outreach

• Screen candidates for technical capability, experience and long term fit

• Partner with engineering leaders to define hiring priorities and role requirements

• Maintain clear tracking of hiring pipelines and delivery progress

• Support wider Talent Solutions activity during peak delivery phases

• Ensure a professional and consistent candidate experience

• Champion fair and inclusive hiring practices

Key Experience

• Proven experience hiring across complex engineering environments

• Strong track record building pipelines across software and infrastructure roles

• Comfortable engaging with technical stakeholders and discussing engineering topics

• Excellent communication and stakeholder management skills

• Strong organisation with the ability to manage multiple roles simultaneously

What We Offer

• Competitive salary and benefits

• Opportunity to support one of the fastest growing AI infrastructure build programmes globally

• Growth within a high performing delivery focused team

• Hybrid working model

• A collaborative culture that values ownership, pace and problem solving

Additional Requirements

• Ability to commute to the San Francisco office

• No visa sponsorship available

• Hybrid working model

About Pinterest:

Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we're on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product.

Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other's unique experiences and embrace theflexibility to do your best work. Creating a career you love? It's Possible.

At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we're looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we'll explore your foundational skills and how you collaborate with AI.

Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here.

We're seeking an Engineering Manager to build and lead the next generation of Pinterest's big data storage platform. You'll grow and guide a team working with cutting-edge open source technologies-especially Apache Iceberg-operating at exabyte scale to power the data that helps Pinners discover and do what they love.

What you'll do:

• 
  
• Own the technical vision and long-term roadmap of Pinterest's exabyte data lake storage
  
• Collaborate with stakeholders and partner teams across the organization to architect data lake storage and metadata management technologies to unlock big data and ML/AI innovations
  
• Drive engagement and collaboration with open source communities, such as Iceberg, Spark, and Flink, to effectively address our scaling challenges
  
• Act as a stalwart of technical quality and excellence on the team, ensuring the solutions we deliver have a high level of polish and reliability
  

What we're looking for:

• 
  
• Bachelor's degree in a relevant field such as Computer Science, or equivalent experience
  
• 2+ years of management experience, or 3+ years tech lead experience in a 5+ person team
  
• 8+ years of relevant industry experience in leading the design of large scale & production distributed systems.
  
• Deep knowledge with building distributed systems.
  
• Strong cross-functional collaborator and communicator.
  
• Strong people development skills.
  
  

In-Office Requirement Statement:

• 
  
• We let the type of work you do guide the collaboration style. That means we're not always working in an office, but we continue to gather for key moments of collaboration and connection.
  
• This role will need to be in the office for in-person collaboration 1-2 times/quarter and therefore can be situated anywhere in the country.
  

Relocation Statement:

• 
  
• This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model.
  

#LI-HYBRID

#LI-AH2

At Pinterest we believe the workplace should be equitable, inclusive, and inspiring for every employee. In an effort to provide greater transparency, we are sharing the base salary range for this position. The position is also eligible for equity. Final salary is based on a number of factors including location, travel, relevant prior experience, or particular skills and expertise.

Information regarding the culture at Pinterest and benefits available for this position can be found here.

Our Commitment to Inclusion:

About Pinterest:

Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we're on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product.

Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other's unique experiences and embrace theflexibility to do your best work. Creating a career you love? It's Possible.

At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we're looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we'll explore your foundational skills and how you collaborate with AI.

Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here.

With more than 500 million users around the world and 300 billion ideas saved, Pinterest Machine Learning engineers build personalized experiences to help Pinners create a life they love. With just over 3,000 global employees, our teams are small, mighty, and still growing. At Pinterest, you'll experience hands-on access to an incredible vault of data and contribute large-scale recommendation systems in ways you won't find anywhere else.

What you'll do:

• 
  
• Build cutting edge technology using the latest advances in deep learning and machine learning to personalize Pinterest
  
• Partner closely with teams across Pinterest to experiment and improve ML models for various product surfaces (Homefeed, Ads, Growth, Shopping, and Search), while gaining knowledge of how ML works in different areas
  
• Use data driven methods and leverage the unique properties of our data to improve candidates retrieval
  
• Work in a high-impact environment with quick experimentation and product launches
  
• Keeping up with industry trends in recommendation systems
  

What we're looking for:

• 
  
• 4+ years of industry experience applying machine learning methods (e.g., user modeling, personalization, recommender systems, search, ranking, natural language processing, reinforcement learning, and graph representation learning)
  
• End-to-end hands-on experience with building data processing pipelines, large scale machine learning systems, and big data technologies (e.g., Hadoop/Spark)
  
• Degree in computer science, machine learning, statistics, or related field
  
• Nice to have:
  
  • 
    
  • Publications at top ML conferences
    
  • Expertise in scalable realtime systems that process stream data
    
  • Passion for applied ML and the Pinterest product
    
  • MS/PhD in Computer Science, ML, NLP, Statistics, Information Sciences, related field, or equivalent experience.
    
  
  
  

Relocation Statement:

• 
  
• This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model.
  

#LI-SA1

#LI-REMOTE

At Pinterest we believe the workplace should be equitable, inclusive, and inspiring for every employee. In an effort to provide greater transparency, we are sharing the base salary range for this position. The position is also eligible for equity. Final salary is based on a number of factors including location, travel, relevant prior experience, or particular skills and expertise.

Information regarding the culture at Pinterest and benefits available for this position can be found here.

Our Commitment to Inclusion:

About Pinterest:

Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we're on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product.

Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other's unique experiences and embrace theflexibility to do your best work. Creating a career you love? It's Possible.

At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we're looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we'll explore your foundational skills and how you collaborate with AI.

Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here.

With more than 500 million users around the world and 300 billion ideas saved, Pinterest Machine Learning engineers build personalized experiences to help Pinners create a life they love. With just over 3,000 global employees, our teams are small, mighty, and still growing. At Pinterest, you'll experience hands-on access to an incredible vault of data and contribute large-scale recommendation systems in ways you won't find anywhere else.

What you'll do:

• 
  
• Build cutting edge technology using the latest advances in deep learning and machine learning to personalize Pinterest
  
• Partner closely with teams across Pinterest to experiment and improve ML models for various product surfaces (Homefeed, Ads, Growth, Shopping, and Search), while gaining knowledge of how ML works in different areas
  
• Use data driven methods and leverage the unique properties of our data to improve candidates retrieval
  
• Work in a high-impact environment with quick experimentation and product launches
  
• Keeping up with industry trends in recommendation systems
  

What we're looking for:

• 
  
• 2+ years of industry experience applying machine learning methods (e.g., user modeling, personalization, recommender systems, search, ranking, natural language processing, reinforcement learning, and graph representation learning)
  
• End-to-end hands-on experience with building data processing pipelines, large scale machine learning systems, and big data technologies (e.g., Hadoop/Spark)
  
• Degree in computer science, machine learning, statistics, or related field
  
• Nice to have:
  
  • 
    
  • M.S. or PhD in Machine Learning or related areas
    
  • Publications at top ML conferences
    
  • Expertise in scalable realtime systems that process stream data
    
  • Passion for applied ML and the Pinterest product
    
  
  
  

Relocation Statement:

• 
  
• This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model.
  

#LI-SA1

#LI-REMOTE

At Pinterest we believe the workplace should be equitable, inclusive, and inspiring for every employee. In an effort to provide greater transparency, we are sharing the base salary range for this position. The position is also eligible for equity. Final salary is based on a number of factors including location, travel, relevant prior experience, or particular skills and expertise.

Information regarding the culture at Pinterest and benefits available for this position can be found here.

Our Commitment to Inclusion:

Job Description:

Mandatory to have working experience as SRE manager especially in Retail domain application support ( NOT CLOUD /DevOps)

Must have working knowledge on SRE principles such as Logs, metrics, availability metrics, uptime, ticket tracking, e-com services, ITIL framework specifically on Alerts, Incident, change management, CAB, Production deployments, Risk and mitigation plan, SLA, SLI, SLO

Hands on experience in Monitoring, Logging, Alerting, Dashboarding, and report generation in any observability tools Prefer DataDog or other tools such as Splunk/Dynatrace/ELK/Grafana). This engagement is a customer using Dynatrace,Splunk, PagerDuty hence it is good to have this expertise

Mandatory to have work experience in leading Level 2/Level 3 application support team based out of IND who provide 24x7 coverage.

Should know how to gather & communicate SRE requirement from customers and define SRE roadmap.

Working experience on how to gather requirements on health of applications, services to monitor, setting service levels.

Must have good knowledge on eCommerce platforms in microservice architecture, Sterling OMS , Retail Applications like XStore.

Should be able to lead P1 calls, brief about the P1 to customer, proactive in gathering leads/ customers into the P1 calls till RCA, PIR etc.

Should have knowledge on building process , framework by following ITSM principles, SOP, runbooks, handling any ITSM platforms (JIRA/ServiceNow/BMC Remedy)

Must know how to work with the Dev team, cross functional teams.

Should be able to generate WSR/MSR by extracting the tickets from ITSM platforms, present to customers and client leaders.

Manage overall SRE delivery, customer focus mindset , closely work with customer leaderships.

Preferred:

Be a client face at customer site collaborating with client leadership.

Ability to clearly communicate and understand a technical idea/concept.

Ability to work in a professional environment while interacting with peers and stakeholders, collaborating with offshore teams.

Excellent written and verbal communications skills.

Motivated, goal driven, influential, innovative, curious, and open minded, fun to work with, collaborator.

Capability to work with people in different time zones.

Ability to operate in a fast-paced, evolving environment and appropriately prioritize tasks, and keep abreast of the latest technology.

Collaborate with cloud architecture, infrastructure team, project management team, and technology services, management team.

Create and maintain detailed documentation.

Mid-Level Technical Writer (Engineering SME)

Palo Alto, CA

Hybrid

Role Summary

The Mid-Level Technical Writer will support the development of validation test reports, test plans, procedures, and related documentation in close coordination with Auto OEM engineering teams and the Senior Lead. The role requires technical fluency and the ability to transform raw data and engineering input into clear, organized, and accurate documentation.

Key Responsibilities

• Prepare and update validation test reports based on engineering inputs and test data
• Support creation and maintenance of test plans, procedures, and setup documentation
• Organize complex technical information into structured report formats
• Work with engineering teams to ensure documentation accuracy and completeness
• Support revisions, document updates, and alignment to agreed templates and standards
• Assist in creation of diagrams, visuals, and setup descriptions as needed
• Track and manage assigned work using Auto OEM tools and workflows

Required Qualifications

• Bachelor's degree in engineering or a related technical field
• Experience in technical writing for engineering, manufacturing, testing, or product development environments
• Ability to understand engineering concepts and translate them into well-structured technical documents
• Experience supporting documentation such as test reports, test plans, procedures, work instructions, or validation records
• Strong written communication and organizational skills
• Must be able to work in a hybrid onsite U.S. model

Preferred Qualifications

• Prior experience in automotive or EV programs
• Exposure to validation, systems engineering, hardware testing, or product verification documentation
• Experience supporting technical diagrams or setup illustrations

Role: Forward Deployment Engineer

Location: Bay Area, CA (Hybrid / Local Candidates Only)

Duration: 6-Month Contract

Position Overview

We are seeking a Forward Deployment Engineer to work closely with customers to rapidly diagnose, develop, and deploy technical solutions that address real-time user issues. This role requires a hands-on full-stack engineer who can quickly understand customer workflows, translate business problems into technical solutions, and implement fixes within extremely short turnaround times.

The ideal candidate will be comfortable working in highly dynamic environments, collaborating directly with end users and product teams to identify problems, architect solutions, and deploy updates rapidly. The role requires a strong ability to leverage modern development approaches, including rapid prototyping and vibe-coding or similar fast iteration techniques, to resolve customer issues within tight timelines.

Key Responsibilities

• Work directly with customers and internal stakeholders to identify and diagnose real-time user issues within deployed systems.
• Translate user needs and operational challenges into technical solutions and rapid fixes.
• Design, develop, and deploy full-stack solutions to resolve customer problems quickly.
• Implement rapid iterations using modern development practices such as vibe-coding, rapid prototyping, and accelerated deployment workflows.
• Deliver production-ready fixes and enhancements within short turnaround windows (often within 12 hours).
• Collaborate with engineering, product, and customer teams to ensure solutions align with platform architecture and long-term product strategy.
• Monitor deployed solutions, gather feedback from users, and continuously improve system performance and usability.
• Document solutions and contribute improvements back into the core product or platform.

Required Qualifications

• Strong experience as a full-stack software engineer with hands-on development experience.
• Ability to quickly diagnose technical issues and design solutions in real time.
• Experience building and deploying applications across both frontend and backend components.
• Comfortable working directly with customers and understanding real-world user workflows and operational challenges.
• Experience with rapid development and deployment methodologies.
• Strong problem-solving skills and the ability to operate effectively in fast-paced, high-pressure environments.

Preferred Qualifications

• Experience working in forward deployment engineering, solution engineering, or customer-facing engineering roles.
• Familiarity with modern development stacks and cloud-based architectures.
• Experience with rapid prototyping tools, AI-assisted coding, or accelerated development frameworks.
• Background working in high-growth technology companies or enterprise SaaS environments.