{"id":2057032,"url":"https://alion.io/job/friendliai-forward-deployed-engineer-ai-inference","title":"Forward Deployed Engineer - AI Inference","company":{"id":673295,"name":"FriendliAI","domain":"friendli.ai","url":"https://alion.io/company/friendli","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":{"grade":"C","score":64,"open_postings":15,"ghost_share":0.6,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-10-15T05:46:00Z"}},"role":"Solutions","role_family":"Solutions","seniority":"middle","employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["San Francisco, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":123000,"max_usd":254000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":426},"experience_years_min":3,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Amazon EKS","optional":false},{"name":"AWS","optional":false},{"name":"CI/CD","optional":false},{"name":"Docker","optional":false},{"name":"GCP","optional":false},{"name":"Helm","optional":false},{"name":"Kubernetes","optional":false},{"name":"LLM","optional":false},{"name":"Multimodal AI","optional":false},{"name":"Platform Engineering","optional":false},{"name":"Terraform","optional":false},{"name":"DeepSpeed","optional":true},{"name":"Diffusion Models","optional":true},{"name":"Function Calling","optional":true},{"name":"Grafana","optional":true},{"name":"Loki","optional":true},{"name":"Prometheus","optional":true},{"name":"SOC 2","optional":true},{"name":"TensorRT","optional":true},{"name":"Tool Use","optional":true},{"name":"Triton","optional":true},{"name":"vLLM","optional":true}],"status":"live","first_seen_at":"2026-10-07T22:53:21Z","employer_posted_date":"2026-10-07","last_verified_at":"2026-10-15T23:58:53Z","board_verified":true,"closed_at":null,"days_open":8,"trust":{"level":"ok","repost_count":0,"flags":["company_stale"],"days_open":7},"description":"About the job\nFriendliAI is seeking a Forward Deployed Engineer to assist enterprises in deploying, scaling, and operating generative and agentic AI workloads on FriendliAI infrastructure. You will work directly with customers to solve and implement production-grade applications using our products, such as Serverless Endpoints, Dedicated Endpoints, or Container.\nFriendli Container is our service that allows customers to download our inference engine as Docker images and deploy it in their chosen environment, such as private clouds or on-premises. Our Friendli Container can be adopted directly to AWS EKS clusters using our EKS add-on product.\nYou will work directly on our customers’ projects, collaborating with their engineering teams to solve AI inference challenges like scaling, orchestration, and monitoring. This is a hands-on, customer-embedded role. If you have worked in DevOps, platform engineering, or SRE for AI applications, this is your ideal position.\nKey Responsibilities\nDesign and implement large-scale deployment architectures for LLM and multimodal inference\n\nDeploy and manage containerized workloads across Kubernetes clusters\n\nDiagnose production issues, such as performance bottlenecks, and implement temporary fixes as needed\n\nCollaborate with customers’ DevOps teams to integrate FriendliAI’s infrastructure into their CI/CD workflows\n\nDevelop scripts, Helm charts, and Terraform modules that simplify repeated deployments\n\nContribute field insights to shape our platform reliability, observability, and scaling strategies\n\nLead workshops, technical sessions, or webinars to help customers master infrastructure best practices.\n\nQualifications\n3+ years of experience in cloud infrastructure, DevOps, or reliability engineering\n\nBachelor’s or Master's degree in Computer Science, Computer Engineering, Electrical Engineering, or equivalent\n\nProficiency with Kubernetes, Docker, Terraform, and Helm\n\nStrong foundation in distributed systems, networking, and performance tuning\n\nExperience with GPU-based computing and generative AI model serving workloads\n\nStrong technical background in backend systems or AI tooling\n\nExperience operating workloads on AWS, GCP, or OCI\n\nExcellent problem-solving and debugging skills in real-world environments\n\nPreferred Experience\nExperience deploying large models (LLMs, diffusion models) on GPUs or clusters\n\nFamiliarity with inference frameworks (Triton, vLLM, TensorRT, DeepSpeed-Inference)\n\nFamiliarity with observability stacks (Prometheus, Grafana, Loki, ELK, OTEL)\n\nUnderstanding of networking security and compliance frameworks (e.g., SOC 2)\n\nExperience supporting on-prem or hybrid-cloud deployments\n\nBenefits\nA front-row seat to the generative AI infrastructure revolution\n\nCompetitive compensation and benefits package\n\nDaily lunch and dinner provided; unlimited snacks and beverages\n\nHealth check-up and top-tier hardware support\n\nFlexible working hours and a highly collaborative environment\n\nAbout us\nFriendliAI is the fastest inference cloud for agents, built to run frontier open-weight models in production at scale. It delivers up to 7x faster output token speed, up to 90% lower inference costs, and 99.99% uptime across the most demanding agent workloads - long-context inference, real-time streaming, and accurate tool calling.\nWe are a small, fast-moving team doing work that matters at one of the most exciting moments in the history of technology. 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