Description

• Python & Node.js Development
• Postgres
• AWS
• AI: Claude, Copilot
• Security experience listed in the JD not needed but nice to have
• Will be communicating with stakeholders, gathering requirements. Needs strong written and verbal comm skills. 
• Will work on integrations with other platforms. 

Client is a national private lender specializing in business-purpose loans for residential real estate

investors. We are modernizing how private lending operates by streamlining underwriting, processing, closing, and

servicing through intelligent automation, data-driven insights, and applied AI.

We are seeking an AI & Automation Implementation Developer to lead the next phase of technology

transformation. This role combines hands-on software engineering, cloud implementation, systems integration, and

applied AI across Salesforce, Encompass, SharePoint, Excel-based processes, internal databases, vendor

platforms, and an AWS-based intelligent document processing (IDP) environment.

You will work closely with the Director of IT, COO, Salesforce developers, Encompass administrators, Compliance,

and operational teams to deliver secure, production-grade capabilities for document ingestion, OCR, data

extraction, LLM-assisted analysis and narratives, business rules, human-in-the-loop quality control, APIs,

dashboards, and workflow automation.

Target Technology Environment

• Languages & APIs Python, JavaScript/Node.js, PowerShell, VBA, REST/GraphQL, webhooks, JSON/XML
• AWS application platform ECS, Lambda, Application Load Balancer (ALB) / API Gateway, Step Functions
• Data & storage Amazon RDS for PostgreSQL (recommended), SQL/JSONB, Amazon S3, DynamoDB where
• appropriate
• Messaging & events SQS, SNS, EventBridge, worker services, retries, idempotency, and dead-letter queues
• AI & document processing Amazon Textract, Amazon Bedrock, GPT/LLM integrations, OCR/NLP, prompt and rules integration
• Security & identity VPC, IAM, KMS, Secrets Manager, Security Groups, S3 SSE-KMS, Okta/Cognito
• Edge & observability CloudFront/WAF, HTTPS and certificate management, Route 53, CloudWatch, OpenTelemetry/XRay
• Enterprise integrations Salesforce, Encompass, SharePoint, Excel, document repositories, and vendor APIs
• Candidates are not expected to be equally deep in every component. Strong hands-on depth in Python, AWS application services, PostgreSQL,
• enterprise integration, and document AI is essential.

Key Responsibilities

AI & Automation Strategy and Delivery

· Partner with leadership to identify and prioritize automation opportunities across sales, underwriting, processing,

closing, post-close, servicing, and draw operations; quantify expected efficiency, quality, risk, and ROI.

· Translate the target architecture and business requirements into implementation plans, proof-of-concepts, pilot

releases, and production-ready services.

· Evaluate and integrate third-party AI and automation vendors, including document classification, data extraction,

underwriting-assist, workflow, and quality-control tools.

· Develop, deploy, and maintain internal automations using Python, JavaScript/Node.js, PowerShell, VBA, RPA, APIs,

and cloud-native services.

Intelligent Document Processing and Applied AI

· Build end-to-end document workflows covering secure upload and ingestion, classification, Amazon Textract OCR,

data extraction, validation, Amazon Bedrock or other LLM/NLP processing, summaries, insights, and documentgroup

narratives.

· Create reusable prompt templates, reference artifacts, processing rules, evaluation datasets, and versioned

configurations that support repeatable and auditable AI behavior.

· Implement human-in-the-loop review, quality-control checkpoints, confidence thresholds, exception queues, reviewer

overrides, and traceability for document decisions.

· Design and enhance rules-engine and rules-interface capabilities for rule sequencing, referencing, conditional

execution, and operational maintenance.

· Establish measurable quality standards for extraction accuracy, exception rate, processing latency, throughput, and

human-review rate.

AWS Cloud and Backend Engineering

· Build and operate Python services on Amazon ECS and/or AWS Lambda, and collaborate on a Node.js web user

interface and supporting services.

· Develop secure REST endpoints behind an Application Load Balancer or API Gateway for document get/put

operations, extracted data, metadata, summaries, insights, and group narratives.

· Implement workflow orchestration with AWS Step Functions and background worker services for document

processing, underwriting runs, and integration jobs.

· Build asynchronous and event-driven patterns using SQS, SNS, and EventBridge, including retries, idempotency,

dead-letter queues, replay, and failure reconciliation.

· Collaborate with infrastructure teams on VPC deployment patterns using public ingress and private application/data

subnets, private endpoints, and secure corporate connectivity.

Data, Storage, and Analytics

· Design and maintain Amazon RDS for PostgreSQL schemas for transactional state, operational data, document

metadata, integration state, KPIs, and processing metrics; use relational modeling, SQL, and JSON/JSONB

appropriately.

· Implement Amazon S3 document storage using pre-signed URLs, versioning, retention controls, lifecycle policies,

and SSE-KMS encryption while maintaining authoritative metadata in PostgreSQL.

· Use DynamoDB or other fit-for-purpose data stores where serverless state, high-volume key-value access, or

workflow patterns warrant it.

· Build dashboards and analytics for operational status, queue health, processing outcomes, accuracy, KPIs, and

automation value realization.

Development and Enterprise Integration

· Design and build integration services connecting Salesforce, Encompass, SharePoint, Excel, internal databases,

document repositories, and vendor platforms.

· Implement a reliable Salesforce synchronization service with durable retries, dead-letter handling, reconciliation, and

clear operational visibility.

· Build and manage REST/GraphQL APIs, webhooks, Encompass SDK integrations, authentication flows, data

mappings, and contract validation between systems.

· Collaborate with Salesforce and Encompass administrators to design trigger-based automations that reduce

repetitive work without weakening data quality or controls.

· Create automated unit, integration, and data-validation tests for APIs, extraction logic, rules, and system-to-system

workflows.

Security, Reliability, and Operations

· Implement least-privilege IAM, KMS key management, Secrets Manager, Security Groups, encryption at rest and in

transit, S3 SSE-KMS, and role-based access using Okta and/or Amazon Cognito.

· Support secure HTTPS delivery and edge controls using CloudFront, WAF, certificate management, Route 53, and

related AWS services in partnership with infrastructure and security teams.

· Implement CloudWatch logs, metrics, alarms, correlation identifiers, dashboards, and alerting; introduce

OpenTelemetry and/or AWS X-Ray when deeper tracing is needed.

· Design for production resilience through Multi-AZ PostgreSQL, backups and recovery, retention, audit logging,

graceful degradation, and operational runbooks.

· Document architecture, API contracts, data flows, configuration, security controls, dependencies, deployment

procedures, and troubleshooting guidance.

AI Enablement and Cross-Functional Capability Building

• Partner with operational teams to convert manual entity review, document review, and data-validation tasks into wellgoverned

AI-assisted workflows.

• Collaborate closely with IT, Compliance, Underwriting, Processing, Closing, Servicing, and Draw teams to ensure

solutions reflect real operating needs and regulatory expectations.

• Act as technical lead for vendor integrations, including technical due diligence, security review, data-flow mapping,

delivery oversight, and acceptance criteria.

• Provide mentorship, code review, documentation standards, and knowledge sharing to strengthen Temple View
• Capital's long-term internal AI and automation capability.
• Work with the Director of IT to track milestones, delivery risk, operating metrics, user adoption, and realized

automation ROI.

Qualifications

Required Skills

• Strong production programming foundation in Python, with working capability in JavaScript/Node.js and at least one

of PowerShell, VBA, or a comparable automation language.

• Hands-on AWS application-delivery experience using several of the following: Amazon RDS for PostgreSQL, S3,

Lambda, ECS, SQS, IAM, KMS, and Secrets Manager.

• Practical PostgreSQL experience, including relational data modeling, SQL, JSON/JSONB, schema migrations,

indexing, query tuning, and transactional design.

• Experience designing and supporting REST APIs, webhooks, asynchronous workers, event-driven integrations,

queue-based processing, retries, idempotency, and dead-letter handling.

• Working knowledge of intelligent document processing, OCR, LLM-based automation, prompt engineering, extraction

validation, and production evaluation techniques.

• Experience with Amazon Textract and Amazon Bedrock, or equivalent OCR and managed LLM platforms, with the

ability to adapt patterns across providers.

• Familiarity with Salesforce APIs, Encompass SDK, document-management systems, and enterprise data

integrations.

• Strong understanding of cloud security fundamentals, including IAM, encryption, secrets management, private
• networking, auditability, and secure handling of sensitive data.
• Experience building automated tests and operational monitoring for production-grade automation and integration
• services.
• Strong documentation and communication skills, with the ability to translate business and compliance requirements
• into maintainable technical implementations.

Preferred Skills

• Experience with AWS Step Functions, SNS, EventBridge, DynamoDB, API Gateway, Application Load Balancer, and
• container-based or serverless workflow orchestration.
• Experience building or supporting Node.js web applications, document viewers, rules interfaces, and operational

dashboards.

• Familiarity with Okta or Amazon Cognito, CloudFront/WAF, Route 53, certificate management, VPC networking,

private endpoints, and Transit Gateway connectivity patterns.

• Experience with CloudWatch, OpenTelemetry, AWS X-Ray, structured logging, distributed tracing, and production

alerting.

• Experience implementing human-in-the-loop review, rules engines, document quality-control workflows, and auditready
• AI decision support.
• Background in mortgage technology, fintech, loan origination systems, underwriting, or regulated financial services.
• Understanding of machine-learning workflows, vector databases, retrieval patterns, data annotation, and evaluation

pipelines.

• Familiarity with LLM integrations beyond Bedrock, such as OpenAI, Azure AI, or Anthropic.
• Experience with UiPath, Power Automate, or similar RPA frameworks, and experience leading small development or

automation projects

Key Skills

Education

Bachelor's degree