Remote opportunity at
NeuraFlashSr. AWS Developer, Products
NeuraFlash, part of Accenture, builds AI, AWS and Salesforce solutions, including conversational AI, predictive analytics and generative tools. The company says it was the only partner…
Career Tools
About This Role
NeuraFlash, part of Accenture, builds AI, AWS and Salesforce solutions, including conversational AI, predictive analytics and generative tools. The company says it was the only partner included in Agentforce's pre-launch private beta and is now a top Salesforce partner for that product. This senior AWS developer role is on the Products team. The Products group develops the core AI engine behind Pulse, a platform for monitoring, insights and evaluation of…
Job Description
NeuraFlash, part of Accenture, builds AI, AWS and Salesforce solutions, including conversational AI, predictive analytics and generative tools. The company says it was the only partner included in Agentforce's pre-launch private beta and is now a top Salesforce partner for that product. This senior AWS developer role is on the Products team.
The Products group develops the core AI engine behind Pulse, a platform for monitoring, insights and evaluation of AI agents, and for NeuraFlash Desktop, a contact center suite built on Amazon Connect. The position is product engineering for AI: building LLM pipelines, agent services and MCP interfaces that let customers evaluate and improve AI agents using real contact center conversations.
Typical tasks include ingesting conversations, detecting topics, scoring outputs with LLM-based evaluators, redacting PII, and generating recommendations. The engineer builds on Amazon Bedrock, including agents, AgentCore, knowledge bases for retrieval, and guardrails, as well as third-party LLM APIs. The role also covers serverless AWS back ends, infrastructure as code with AWS CDK, the Amazon Connect integration layer, and security practices such as authentication, least-privilege access and encryption.
The ideal candidate has at least five years of experience, strong Python or TypeScript and Node.js skills, and production experience with generative AI and Bedrock. They should be comfortable with serverless AWS design and Amazon Connect, bring a security-first mindset, and be ready to lead code reviews, mentor others and own product work with little direction.
Responsibilities
- Develop Pulse's core AI features: conversation ingestion, topic detection, LLM-driven grading, PII redaction, and an insights engine that gives recommendations
- Work with Amazon Bedrock services (agents, AgentCore, knowledge bases, guardrails) and third-party LLM APIs
- Create an MCP server and agent-oriented interfaces so assistants and customer tools can access Pulse data and actions
- Build observability for agents: session and trace capture, evaluation frameworks, quality scores and health indicators
- Develop serverless back-end services on Lambda, API Gateway, DynamoDB, Aurora or RDS, S3, Kinesis and Step Functions
- Own infrastructure-as-code using AWS CDK, delivering hardened components that deploy into customer accounts
- Lead the Amazon Connect integration: contact records, Contact Lens data, agent event feeds, Lex bots and flow touchpoints
- Strengthen security through Cognito/OIDC, least-privilege IAM, encryption, and fixing scan findings
- Review code, mentor developers and own product epics end to end
Requirements
- At least five years of experience
- Coding ability in Python or TypeScript with Node.js
- Practical GenAI application work: prompt design, retrieval-augmented generation, structured outputs, LLM-based judging, guardrails and cost tuning
- Production use of Amazon Bedrock or a similar LLM platform
- Substantial serverless AWS experience across Lambda, API Gateway, DynamoDB, S3 and event buses
- Working knowledge of AWS CDK or CloudFormation, plus CI/CD
- Amazon Connect experience: flows, Lex, and CTR or Contact Lens streams
- Track record building AI agents on Amazon Connect, Lex and Bedrock for voice or chat self-service and agent assist
- Building and running REST APIs and event-based integrations
- Security-first habits: IAM, Cognito, KMS encryption, VPC design and a secure development lifecycle
Qualifications
- AWS Developer or Solutions Architect certification at associate or professional level
- Familiarity with MCP servers or agent frameworks such as AgentCore, LangGraph, Strands or CrewAI
- Evaluation and tracing experience for AI agents
- Multi-tenant SaaS or deployments into customer cloud accounts
- Knowledge of contact center platforms, including workforce tools, WebRTC and SIP
- Some Salesforce platform knowledge, covering Service Cloud, Data Cloud and Agentforce
- An AWS AI Practitioner or ML Specialty credential
Core Skills
Benefits
- Remote or in-office options, with headquarters in Massachusetts and hubs in several regions
- Travel up to 25 percent for some positions
- Results-based flexibility rather than rigid hours
- Company town halls where leaders answer every question
- Team celebrations and social gatherings
Frequently Asked Questions
Answers are based only on the employer’s listing; where it doesn’t say, neither do we.
Is this role remote?
The listing says remote. The posting describes remote and in-person options, with headquarters in Massachusetts, but gives no specific location for this role.
What is the salary?
The posting gives no salary figure.
What experience is required?
The posting requires at least five years, hands-on Python or TypeScript with Node.js, production GenAI or LLM work, and Amazon Bedrock experience.
Is travel required?
Some positions involve travel up to 25 percent; the posting does not say what applies to this one.
Sample Interview Questions
AI-generated questions tailored to this specific role — a preview of the full practice set.