Forward Deployed Engineer jobs in Israel

About Chalk Chalk (chalk.ai) is the platform for production AI. Trusted by enterprises including Whatnot, Grindr, Mission Lane, Turo, and Apartment List, Chalk brings together context, runtime, and learning for agents and models. Chalk’s Context Engine delivers live context by querying data across warehouses, databases, streams, and APIs, straight from the source. Chalk’s runtime powers agents and models with infrastructure and governed access to LLMs and tools. Together, these capabilities help teams build AI that understands their business, continuously improves, and runs reliably in production. We've recently raised a $50 million Series A, led by Felicis. Learn more at chalk.ai. About the role You are an exceptional Software Engineer who wants to work directly alongside the people using what you build. As a Forward Deployed Engineer, you will be embedded with our customers' data engineering, data science, and machine learning teams and write code that connects Chalk to their unique infrastructure and use cases. As the subject matter expert in the room, you will work with these data teams to build efficient ML and AI systems. When a customer needs something that Chalk doesn't do yet, you will prove out that new capability and personally build the first version into our platform, where it becomes available to every customer. Your work will power use cases like cancer detection, fraud prevention, and product recommendation. This is your opportunity to join us in-person as an early employee and make a significant impact at a high growth start-up. What you will do • Write code across the entire code base to implement Chalk technology for Chalk customers and prospects. You will become familiar with Chalk infrastructure and find the best way to integrate and implement them in different environments • Discover customer's needs and then design, implement, and ship new features for customers • Work closely with our Engineering and Sales teams • Act as the primary technical point of contact pre-sales and post-sales (when we are onboarding a new customer or supporting an existing one) • Recommend new products to customers as their business evolves • Help interview and grow the Engineering team What we’re looking for • Technical background including experience writing software or building ML models • 4+ years experience of professional backend software engineering experience • Proficient in Python, SQL • Ability to collaborate effectively in teams of technical and non-technical individuals • Excellent written and verbal communication, problem-solving, storytelling, and analytical skills • Experience working closely with sales teams and customers is a plus. • Bachelor's degree in Computer Science or equivalent Bonus points • Previous experience working with ML/data products or services • Understanding of Machine Learning Ops/Infrastructure • Previous experience as a forward-deployed engineer in a high-growth startup focusing on Machine Learning.

About Telnyx Telnyx is an industry leader that's not just imagining the future of global connectivity—we're building it. From architecting and amplifying the reach of a private, global, multi-cloud IP network, to bringing hyperlocal edge technology right to your fingertips through intuitive APIs, we're shaping a new era of seamless interconnection between people, devices, and applications. We're driven by a desire to transform and modernize what's antiquated, automate the manual, and solve real-world problems through innovative connectivity solutions. As a testament to our success, we're proud to stand as a financially stable and profitable company. Our robust profitability allows us not only to invest in pioneering technologies but also to foster an environment of continuous learning and growth for our team. Our collective vision is a world where borderless connectivity fuels limitless innovation. By joining us, you can be part of laying the foundations for this interconnected future. We're currently seeking passionate individuals who are excited about the opportunity to contribute to an industry-shaping company while growing their own skills and careers. The Role We're building a local Enterprise Sales Pod in Tel Aviv — one AE and one Forward Deployed Engineer (FDE), working together to build a Telnyx enterprise business in your market. You'll embed directly with enterprise customers to architect and ship production systems on Telnyx's global network — voice, messaging, AI, and wireless. This isn't about demoing products. It's about building real solutions that work at scale. You'll work side-by-side with a dedicated Enterprise AE — not a demo resource, but a commercial partner who owns the named-account list, builds executive relationships, and closes the deal. You own the technical side: discovery, architecture, POC, and production go-live. You win together. No throw-over-the-wall. The Pod Model Enterprise AE — owns the named-account list, builds executive relationships, gets in the room, owns commercial qualification and close, expands the account.. Forward Deployed Engineer — owns technical discovery, designs the architecture, builds the POC when gated, gets the first workload live, removes blockers and finds the next workload. We sell the workload, not the SKU. Customers buy a production outcome — an AI contact center, a SOC/NOC agent, global communications, connected mobility, or enterprise inference — that runs on Telnyx primitives (voice, messaging, numbers, wireless, Voice AI, inference, agents, connectivity). You lead with the outcome conversation, not a product menu. What You'll Do • Embed with enterprise customers to understand their communications workflows, AI use cases, and integration challenges firsthand • Build and deploy custom implementations: AI Voice Assistants, Telnyx APIs (Voice, Messaging, Fax, Wireless), WebRTC • Run open-weight LLMs in customer environments — consume GLM, Kimi, DeepSeek, Qwen, and MiniMax through Telnyx Inference (OpenAI-compatible API; there's no model infrastructure for you to run), or deploy self-hosted stacks (Llama, Mistral, and region-specific models like Hebrew-adapted LLMs or other sovereign models) behind your own serving engine when air-gapped or sovereign-cloud requirements demand it • Deploy and operate LiteLLM as the model gateway in customer environments: a unified OpenAI-compatible interface across self-hosted open-weight models and hosted providers, with routing, load balancing, retries and fallbacks, rate limits, and per-team virtual keys • Instrument and govern LLM usage through the gateway — cost tracking and budgets, caching, logging and observability (OpenTelemetry, Langfuse, or similar), and guardrails — so customers can see and control what their AI workloads are doing • Wire production observability for everything you ship — metrics, logs, traces, dashboards, and alerting (e.g. Prometheus + Grafana for metrics, OpenTelemetry for traces, Graylog or ELK for logs — or the customer's existing stack) — so you and the customer's ops team both know what "healthy" looks like and what pages whom when it isn't • Design model routing strategies for real-time voice workloads, balancing latency, cost, and quality, with sane fallback behavior when a provider degrades • Make the build-vs-buy case between self-hosted open-weight models and hosted frontier APIs, and keep the customer's application code portable across both • Adapt models to customer domains: prompt and RAG pipelines and evaluation harnesses for Hebrew and English language use cases and Israel-specific regulatory environments (Privacy Protection Law, data localization requirements, defense/security sector compliance) • Lead POCs, pilots, and production launches from whiteboard to go-live • Own customer outcomes — stay engaged until the solution is live and stable • Collaborate directly with Product and Engineering to shape the roadmap based on field insights from Israel • Create clear technical documentation, runbooks, and maintainable solutions for handoff • Troubleshoot and resolve complex integration issues alongside customer teams What We're Looking For • CS degree or equivalent experience • 3+ years building and shipping production software — you've written code that real users depended on, you've been on-call for it, and you've debugged it when things broke. (A consulting background counts if this is also true of you.) • Proficiency in multiple languages: Python, Node.js/TypeScript, Go — you're more dangerous in some than others. (Telnyx Edge Compute — functions and stateful actors — is TypeScript, so that one pulls double duty.) • Practical understanding of what breaks in front of a model in production: provider rate limits and quotas, timeout and retry behavior, streaming, token accounting and cost attribution, and the failure modes that only show up under concurrency • Comfortable deploying containerized services on Kubernetes, with secrets management, config, and upgrades as part of the deployment story • You've wired observability and been paged because of it — Prometheus + Grafana, OpenTelemetry, Graylog, ELK, or equivalent. You know what to monitor, what to alert on, and what "healthy" looks like • High-concurrency experience — Kafka, message queues, or event streams at real scale. When throughput spikes you know what breaks — consumer lag, backpressure, hot partitions, rebalance stalls — and what absorbs it: partitioning, consumer groups, parallelism up to your partition count • You've built APIs from scratch, not just consumed them — OpenAPI spec, REST/GraphQL design, auth, rate limiting, versioning, idempotency • Event-driven thinking and cloud-native instincts • Exposure to SIP, WebRTC, or real-time voice/messaging systems • Self-sufficient by default — there's no engineering team behind you. You read the code and the docs, ask the customer (not your manager), and make sound engineering judgment calls on your own • Customer-facing engineering experience — you can run discovery with a customer's engineers and present to their executives in the same week • Ability to translate "it's not working" into root cause • Comfortable working on customer sites and in high-stakes technical conversations • Excellent written and verbal communication in English and Hebrew. You can run whiteboard sessions, live troubleshooting, and escalations with customer engineering teams. • Based in Tel Aviv, or willing to relocate — this is a hybrid role with travel across Israel • Legally authorized to work in Israel, or eligible for sponsorship Bonus Points For • Experience with AI voice assistants, STT/TTS, or LLM-based conversational systems • Building eval sets for a specific domain • Hands-on production experience with an LLM gateway — LiteLLM, Portkey, Kong AI Gateway, or an in-house OpenAI-compatible proxy — including config-driven model definitions, routing and fallback rules, and virtual key management • Familiarity with the open-weight model landscape and the trade-offs between regional and multilingual models, including Hebrew-adapted LLMs and Israeli AI initiatives • Experience with an inference serving engine behind the gateway — vLLM, SGLang, or TGI for production serving; Ollama for lightweight on-prem — and sizing GPU capacity for self-hosted models (KV-cache footprint, concurrent batch size, and context length against VRAM) • SQL proficiency (Postgres, MySQL, Oracle) • ETL and data wrangling experience • CI/CD pipeline design and automation • Background in telecom, CPaaS, or high-growth SaaS • Experience with sovereign or on-prem cloud deployments and Israeli regulatory frameworks (Privacy Protection Law, data localization, defense/security sector compliance including IL2/IL3/IL4 classification, dual-use technology export controls) • Security mindset (IAM, encryption, audit logging) #LI-RH1