Software Engineer – GenAI / Agentic AI / Cloud Engineering
Qualifications, skills, and all relevant experience needed for this role can be found in the full description below.
We are seeking a
Software Engineer with 5+ years of experienc e to design and build
AI-driven automation platform s that enhance internal customer engagement and streamline onboarding into enterprise cryptographic services
.
This role focuses on developing Python-based, cloud-native applications leveraging Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), agentic AI workflows, and modern orchestration frameworks such as LangChain and LangGraph to automate manual analysis, understand customer intent, and intelligently guide users to the appropriate cryptographic service
s.
The ideal candidate has strong hands-on experience building production-grade GenAI applications, integrating AI orchestration frameworks, vector search systems, and secure cloud-native microservices in AWS environmen
ts.
Key Responsibili
tiesDesign and develop Python-based AI applications and microservices to automate internal customer engagement, onboarding, and service triage workfl
ows.Build and deploy GenAI-powered solutions using LLMs, embeddings, vector databases, and Retrieval-Augmented Generation (RAG) architectu
res.Design and implement agentic AI workflows using frameworks such as LangChain, LangGraph, LlamaIndex, or equivalent orchestration framewo
rks.Develop intelligent assistants capable of understanding natural language requests, reasoning across enterprise knowledge, and recommending appropriate cryptographic servi
ces.Build and maintain document ingestion pipelines, chunking strategies, embedding workflows, vector indexing, and contextual retrieval systems for enterprise knowledge acc
ess.Implement multi-step AI orchestration pipelines, including planning, tool calling, memory/context handling, and workflow execut
ion.Integrate AI solutions with AWS Bedrock or equivalent foundation model platforms, including model selection, prompt optimization, and inference orchestrat
ion.Develop and maintain cloud-native microservices using AWS services such as Lambda, ECS/EKS, API Gateway, S3, DynamoDB, and event-driven architectu
res.Automate manual analysis, routing, and triage processes using a combination of AI/ML models, deterministic logic, and workflow automat
ion.Collaborate with product, architecture, security, and compliance teams to translate business and regulatory requirements into scalable technical soluti
ons.Monitor, troubleshoot, and optimize production AI workloads for latency, hallucination control, reliability, observability, and cost efficie
ncy.
Required Skills & Exper
ience
5+ years of professional software engineering experience in backend, cloud-native, AI/ML, or platform engine
ering.Strong Python development expertise with frameworks such as FastAPI, Flask, or similar backend frame
works.Hands-on experience building production GenAI applications, not just experimentation or
POCs.Strong experience with LangChain, LangGraph, LlamaIndex, or comparable AI orchestration frame
works.Experience designing and implementing RAG architectures, including ingestion, chunking, embeddings, retrieval optimization, and grounding strat
egies.Hands-on experience with vector databases such as Pinecone, FAISS, Redis, pgvector, OpenSearch, Weaviate, or si
milar.Experience building agentic workflows, tool-calling systems, memory/context management, and autonomous decision work
flows.Solid understanding of prompt engineering, LLM behavior, hallucination mitigation, output validation, and response grounding techn
iques.Experience integrating with AWS Bedrock, OpenAI APIs, Anthropic, or equivalent LLM plat
forms.Strong AWS cloud experience, especially with Lambda, ECS/EKS, S3, DynamoDB, API Gateway, IAM, CloudWatch, and serverless architec
tures.Experience with Docker, Kubernetes, GitHub Actions, CI/CD pipelines, and infrastructure automation (CloudFormation/CDK/Terra
form).Understanding of distributed systems, API design, event-driven architectures, and microser
vices.Experience working in security-sensitive, compliance-heavy, or enterprise regulated environments pref
erred.
Nice
to HaveExperience in cryptography, PKI, certificate management, enterprise security services, or cybersecurity pla
tforms.Exposure to MCP (Model Context Protocol), custom AI tool integrations, or enterprise AI agent fram
eworks.Experience implementing AI observability, evaluation pipelines, or model performance moni
toring. xsgimln Familiarity with secure AI governance and responsible AI pra