Senior Forward Deployed Engineer

Siri InfoSolutions Inc; Mills (AR); On-site; USD 140,000 - 230,000; Full time

Job summary

Siri InfoSolutions Inc in the United States seeks an experienced AI/ML engineer to lead hands-on delivery of Claude-based agentic AI, RAG and LLM solutions on AWS and enterprise platforms. You will partner with business users, architects and data teams to translate needs into working AI products.

You will own solution design for agent workflows, API integrations, prompts and guardrails, and drive MVPs through production hardening, monitoring and cost optimization across asset management use

Qualifications

• 12+ years of software/data engineering with hands-on AI/GenAI delivery.
• Proven Claude-based prototype-to-production experience on Bedrock.
• Strong Python APIs experience with FastAPI/Flask.
• Hands-on with LangChain/LangGraph/LlamaIndex/AutoGen.
• Deep RAG pipelines, embeddings, and semantic search expertise.
• Strong AWS Bedrock, Lambda, API Gateway, and CI/CD knowledge.

Responsibilities

• Lead hands-on build, deployment and productionization of Claude-based AI solutions on AWS and internal platforms.
• Partner with business users and domain SMEs to translate needs into AI products.
• Own design of agent workflows, API/tool integrations, prompts, evaluators and guardrails.
• Drive rapid discovery, MVP delivery and production hardening across asset management use cases.
• Provide technical leadership through reviews, troubleshooting and reusable patterns.
• Integrate AI apps with internal systems, data sources and workflow tools.
• Troubleshoot hallucinations, latency, tool calls and orchestration errors.
• Optimize performance, reliability and cost via caching, routing and monitoring.
• Ensure compliance with security, privacy, governance and model risk requirements.
• Create documentation, deployment runbooks and transition materials.

Skills

AI/ML engineering

Claude/Anthropic

Python development

FastAPI/Flask

LangChain

RAG pipelines

Embeddings/Vector DB

AWS Bedrock

CI/CD

Tool calling / guardrails

Observability

Cost optimization

Asset Management domain

Tools

LangChain

LangGraph

LlamaIndex

AutoGen

Amazon Bedrock

AWS services (S3, Lambda, API Gateway, etc.)

FastAPI

API Gateway

Lambda

S3

CI/CD pipelines

Job description

Must Have Technical/Functional Skills:

• 12+ years of software/data engineering experience with strong hands-on delivery of AI, GenAI, LLM, RAG and agentic AI solutions in enterprise environments.
• Proven experience leading prototype-to-production delivery of Claude based AI solutions, preferably using Anthropic Claude on Amazon Bedrock.
• Strong Python engineering skills with production API development experience using FastAPI, Flask or similar frameworks.
• Hands-on experience with agentic orchestration patterns and frameworks such as LangChain, LangGraph, LlamaIndex, AutoGen or similar.
• Deep experience with RAG pipelines, embeddings, vector databases, semantic search, document ingestion, re-ranking, grounding and LLM evaluation.
• Strong AWS implementation experience across Bedrock, Lambda, API Gateway, Step Functions, ECS/EKS, S3, IAM, KMS, CloudWatch, CloudTrail and CI/CD.
• Experience integrating AI solutions with enterprise APIs, data platforms, workflow platforms, knowledge repositories and in-house capabilities.
• Strong understanding of tool/function calling, MCP servers, guardrails, validation, human-in-the-loop patterns, observability, latency and cost optimization.
• Functional exposure to Asset Management, Investment Operations, Distribution, Client Reporting or Middle Office processes is preferred.

Roles & Responsibilities:

• Lead hands-on build, deployment and productionization of Claude based agentic AI, RAG and LLM solutions on AWS and enterprise internal platforms.
• Partner directly with business users, domain SMEs, architects, security, cloud and data teams to convert ambiguous needs into working AI products.
• Own solution design for agent workflows, API/tool integrations, prompt templates, evaluators, guardrails, human approval flows and exception handling.
• Drive rapid discovery, prototyping, MVP delivery, production hardening and scale-up across prioritized asset management use cases.
• Provide technical leadership to FDEs and engineers through design reviews, code reviews, troubleshooting, reusable patterns and delivery governance.
• Integrate AI applications with internal systems, enterprise data sources, knowledge repositories, workflow tools and API ecosystems.
• Troubleshoot complex live issues including hallucination, retrieval quality, model behavior, latency, failed tool calls, orchestration errors and access constraints.
• Optimize performance, reliability and cost using caching, model routing, batching, prompt tuning, monitoring and architecture improvements.
• Ensure solutions align with enterprise security, IAM, encryption, audit logging, privacy, AI governance and model risk requirements.
• Create technical documentation, implementation plans, deployment runbooks, demos and transition materials for support and long-term adoption.

Generic Managerial Skills, If any:

• Strong client-facing leadership with ability to communicate complex AI solutions clearly to business, domain, architecture and engineering stakeholders.
• Ability to lead in ambiguous environments, structure problem statements and drive fast iterative delivery with measurable outcomes.
• Strong collaboration skills across product owners, SMEs, security, cloud, data, architecture and delivery teams.
• Ownership mindset with ability to independently drive PoCs, MVPs, production fixes, technical decisions and delivery commitments.
• Strong prioritization, risk management, issue escalation and stakeholder alignment skills in live enterprise environments.
• Ability to mentor engineers, establish reusable engineering patterns, enforce code quality and promote disciplined delivery practices.