Forward Deployed Engineer

• Help design, build and continuously improve the clients online platform.
  


• Research, suggest and implement new technology solutions following best practices/standards.
  


• Take responsibility for the resiliency and availability of different products.
  


• Be a productive member of the team.
  

Requirements

• 10+ years of experience in software engineering, infrastructure engineering, or applied ML engineering.
  


• Strong proficiency in Python, TypeScript/JavaScript, or other backend programming languages.
  


• Deep expertise in agent development and agent orchestration techniques.
  


• Hands\-on experience with LangChain, LangWatch, MCP, Vertex AI, and OpenAI platforms.
  


• Proven experience deploying and operating systems on cloud platforms such as AWS, GCP, or Azure using Kubernetes and serverless architectures.
  


• Strong understanding of API design, distributed systems, and data engineering workflows.
  


• Extensive experience with CI/CD pipelines and infrastructure\-as\-code tools such as Terraform, Helm, and Ansible.
  


• Skilled in implementing monitoring, observability, and alerting solutions using tools like Prometheus, Grafana, ELK, or Datadog.
  


• Solid understanding of performance profiling, scaling strategies, and SRE best practices.
  


• Knowledge of enterprise SaaS security models, including SSO, RBAC, encryption, and API security.
  


• Experience working in regulated environments and compliance frameworks such as SOC2, HIPAA, and GDPR.
  


• Excellent debugging and problem\-solving skills, especially in high\-pressure production environments.
  


• Strong communication skills with technical stakeholders, including engineering teams, architects, and senior leadership.
  


• Comfortable working in fast\-paced, ambiguous environments with minimal guidance.
  


• Lead end\-to\-end technical deployments of the PHTN.ai platform within enterprise environments.
  


• Design and implement robust integration pipelines connecting customer data sources, APIs, and systems of record.
  


• Deploy, scale, and monitor machine learning models in production to ensure reliability and performance.
  


• Automate deployments using CI/CD pipelines, infrastructure\-as\-code, and container orchestration technologies such as Docker and Kubernetes.
  


• Develop custom extensions, SDKs, and APIs to tailor the platform for customer\-specific use cases.
  


• Build microservices, tools, and scripts for data preprocessing, feature engineering, and real\-time inference.
  


• Optimize model serving, caching, and resource utilization for low\-latency and high\-throughput workloads.
  


• Apply hands\-on expertise in LangChain, LangWatch, and related Lang ecosystem technologies.
  


• Architect enterprise\-grade solutions with strong resilience, scalability, and observability.
  


• Ensure deployments follow security best practices, including encryption, identity management, and network security.
  


• Address compliance requirements such as SOC2, HIPAA, GDPR, and customer\-specific regulatory standards.
  


• Act as the senior technical lead for customer deployments, resolving complex engineering challenges.
  


• Collaborate closely with customer engineering teams to integrate the platform into production systems.
  


• Provide critical feedback to product and core engineering teams on performance, scalability, and enterprise integration needs.
  


• Create reusable deployment templates, automation scripts, and operational playbooks to accelerate future implementations.
  


• Mentor Forward Deploy Engineers on advanced deployment patterns, DevOps practices, and ML systems engineering.

Benefits

• A challenging, innovating environment.
  


• Opportunities for learning where needed.