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About the role As a Technical Support Engineer at a pioneering AI company, you'll be the first line of defense to support customers as they build out training, fine tuning, and inference solutions with Together AI. You'll dive deep into complex technical challenges, providing swift and effective solutions while serving as a product expert. As a part of the Customer Experience organization, you will collaborate closely with product and sales, driving continuous improvement of our offerings. This is an exciting opportunity for a deeply technical professional passionate about AI and customer success to make a significant impact in a fast-paced, innovative environment. Required hours This is a fulltime position working India daytime hours. The role will work both weekend days (Saturday and Sunday) as well as two additional weekdays. This is a 4-day shift, 10 hours per day, with 2 additional hours of on-call coverage on Saturdays and Sundays. The role would start as a Monday to Friday role for the first few months to allow for ramping up and learning from teammates. After being considered fully ramped, the role would transition to the 4-day weekend shift. Responsibilities Engage directly with customers to tackle and resolve complex technical challenges involving our cutting-edge GPU clusters and our inference and fine-tuning services; ensure swift and effective solutions every time. Act as a customer facing SRE to ensure our customer’s Inference endpoints (running on Kubernetes) remain healthy, stable, and performant Become a product expert in all of our Gen AI solutions, serving as the last line of technical defense before issues are escalated to Engineering and Product teams. Assist with hardware and platform migrations by validating system health and traffic routing. Monitor dashboards to detect anomalies and escalate with data-backed analysis Manage customer-facing communications during incidents and degradations; translate deep technical findings (latency regressions, provider issues, network reachability drops) into clear, evidence-backed updates without exposing platform internals Contribute infrastructure changes for model deployment, capacity rebalancing, and cluster configuration. You will execute infrastructure changes via pull requests (infra-as-code) for tasks such as endpoint configuration, model bringup/bringdown, and capacity scaling Flag engine-level bugs with logs and reproduction steps for engineering Collaborate seamlessly across Engineering, Research, and Product teams to address customer concerns; collaborate with senior leaders both internally and externally to ensure the highest levels of customer satisfaction. Transform customer insights into action by identifying patterns in support cases and working with Engineering and Go-To-Market teams to drive Together’s roadmap (e.g., future models to support) Maintain detailed documentation of system configurations, procedures, troubleshooting guides, and FAQs to facilitate knowledge sharing with team and customers. Be flexible in providing support coverage during holidays, nights and weekends as required by business needs to ensure consistent and reliable service for our customers. Requirements 6+ years of experience in a customer-facing technical role, SRE, DevOps, or infrastructure engineering, with at least 1 year in a support role for an AI service Strong technical background, with knowledge of AI, ML, GPU technologies and their integration into high-performance computing (HPC) environments. Advanced, production-level experience with infrastructure services (e.g., Kubernetes, SLURM), infrastructure as code solutions (e.g., Ansible) high-performance network fabrics, NFS-based storage management, and container infrastructure Familiarity with operating storage systems in HPC environments such as Vast and Weka Proven ability to diagnose complex network-layer issues and read traces Strong knowledge of Python, TypeScript, and/or JavaScript with testing/debugging experience using curl and Postman-like tools Demonstrated expertise with observability tooling (e.g., Prometheus, Grafana) at scale Deep familiarity with REST API debugging and HTTP semantics Experience with LLM inference frameworks and LoRA fine-tuning and common training failure modes Experience with Infrastructure as Code and Git-based workflows Background in GPU cluster management Cloud platform experience (AWS, GCP, and/or Azure) Foundational understanding in the installation, configuration, administration, troubleshooting, and securing of compute clusters. Complex technical problem solving and troubleshooting, with a proactive approach to issue resolution Ability to work cross-functionally with teams such as Sales, Engineering, Support, Product and Research to drive customer success. Strong sense of ownership and willingness to learn new skills to ensure both team and customer success. Excellent communication and interpersonal skills, with the ability to explain complex technical concepts to non-technical stakeholders. Ability to operate in dynamic environments, adept at managing multiple projects, and comfortable with frequent context switching and prioritization. About Together AI Together AI is a research-driven artificial intelligence company. We believe open and transparent AI systems will drive innovation and create the best outcomes for society, and together we are on a mission to significantly lower the cost of modern AI systems by co-designing software, hardware, algorithms, and models. We have contributed to leading open-source research, models, and datasets to advance the frontier of AI, and our team has been behind technological advancement such as FlashAttention, Hyena, FlexGen, and RedPajama. We invite you to join a passionate group of researchers in our journey in building the next generation AI infrastructure. Compensation We offer competitive compensation, startup equity, health insurance, and other benefits, as well as flexibility in terms of remote work for the respective hiring region. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge. Equal Opportunity Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more.
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.