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Farsight AI

AI-driven financial workflow automation SaaS

Professional Services Engineer

Implementation & Technical Account ManagementUpdated on Nov 13
Full-timeNew York, NY, USA

About the Job

Requirements

  • At least 5 years of experience in cloud infrastructure engineering, DevOps, solutions architecture, or professional services and consulting, including a strong customer-facing component.
  • Deep knowledge of AWS services including ECS, EC2, Lambda, S3, CloudFront, CloudWatch, RDS, IAM, SSM, and VPC networking, and experience designing and deploying production workloads on AWS.
  • Strong proficiency with infrastructure-as-code tools including AWS CDK, CloudFormation, and Terraform, and with containerization and orchestration using Docker and Kubernetes.
  • Experience deploying software into enterprise or regulated customer environments, including security reviews, network restrictions, and formal change control processes.
  • Understanding of cloud security and compliance frameworks including SOC 2, GDPR, and ISO, and ability to work with customer security and compliance teams.
  • Ability to explain complex infrastructure concepts to technical and non-technical stakeholders and build trust with senior customer counterparts.
  • Ability to work independently with limited structure, manage multiple customer engagements simultaneously, and work without an existing playbook.
  • Ability to write technical documentation, architecture diagrams, and runbooks.
  • Based in New York City, able to work onsite, and willing to travel to customer sites as needed.

Responsibilities

  • Lead technical delivery of customer deployments across customer VPC, customer cloud, and on-premise environments, from kickoff through production go-live.
  • Partner with customer IT, security, and infrastructure teams to review architecture, network topology, identity and access requirements, and data flows, and drive technical approvals to closure.
  • Support pre-sales technical scoping, including dataflow diagrams, architecture documentation, and responses to security and compliance questionnaires.
  • Work with Strategy and Operations and go-to-market teams to confirm technical feasibility before commitments are made to customers, and communicate constraints in both directions.
  • Build and maintain deployment automation using infrastructure-as-code tools including AWS CDK, CloudFormation, and Terraform to make customer deployments repeatable, auditable, and secure.
  • Design and document runbooks, reference architectures, and onboarding playbooks, and conduct knowledge-transfer sessions so customer teams can operate and maintain their environments.
  • Troubleshoot deployment and integration issues in customer environments, working with Infrastructure and Platform Engineering to resolve root causes and feed fixes back into the product.
  • Represent the technical voice of the customer internally by surfacing recurring deployment friction and customer requirements to inform the infrastructure and product roadmap.
  • Support customer technical escalations and post-deployment health, including monitoring, upgrades, and change-control coordination.

Desired Qualifications

  • Prior experience in professional services, solutions architecture, or a forward-deployed role at a cloud provider or enterprise software company.
  • Experience deploying software into on-premise or air-gapped environments.
  • Experience with customer cloud deployments across AWS, Azure, and Google Cloud Platform.
  • Experience deploying infrastructure for generative AI or machine-learning workloads.
  • Experience in financial services or other heavily regulated industries.

About the Company

Farsight AI

AI-driven financial workflow automation SaaS

Farsight AI builds an AI-powered SaaS platform that automates financial workflows for financial institutions, especially investment banks. It automatically generates strategic materials such as pitch decks, comps, and financial models by integrating with a firm’s CRM data, historical deals, and institutional knowledge. The product works by leveraging AI models (including Azure OpenAI) to analyze existing data and predict analytical needs, producing documents in advance so professionals can focus on higher-value work. It differentiates itself by tailoring automation to the finance domain and pre-creating complex materials from a firm’s own data, rather than providing generic document generation. The company’s goal is to speed up decision-making and improve data-driven strategies, helping firms compete more effectively through streamlined, higher-efficiency workflows.

Company size
11-50
Company stage
Early VC
Total funding
$26.1M
Headquarters
New York City, New York
Founded
2022

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