Conversational AI Engineer

We are looking for a Conversational AI Engineer who combines hands-on platform expertise with a genuine passion for Generative AI. You will analyse client requirements, understand business problems, design autonomous AI agents and bot/agent architectures, create prompts, personas and guardrails, and integrate backend systems through REST APIs and MCP. Design multi-step agentic workflows where AI can reason, plan and execute across systems. Focus on building robust and scalable solutions rather than only completing tickets., * Design scalable bot and agent architectures using Cognigy.AI, Amazon Bedrock AgentCore, Amazon Connect, Amazon Lex, Google CCAI, Kore.ai, Microsoft Bot Framework or Parloa.

• Build deterministic, GenAI and multi-step workflows.
• Validate and transform LLM outputs using JavaScript/TypeScript, Python or Java.
• Integrate CRM, ERP, ticketing, CCaaS and telephony systems through REST, MCP and GraphQL.
• Work with PBX, SBC, TTS and ASR technologies.
• Troubleshoot conversational flows, APIs, LLM behaviour and infrastructure.
• Apply LLM concepts such as context windows, tokens, temperature and embeddings.
• Evaluate and improve prompts.
• Use AI and Agentic Coding tools where appropriate.
• Apply Clean Code, SOLID principles, unit and integration testing.
• Work with Docker, Kubernetes/OpenShift, CI/CD, cloud services and observability tools.
• Follow OWASP-aware secure coding practices

Requirements

• Work proactively with clients and globally distributed, cross-functional teams.
• Participate in code reviews and architecture reviews.
• Convert ambiguous problems into actionable tasks.
• Define success metrics, plans and roadmaps.
• Align project delivery with operations, including availability, backups, monitoring, logging and documentation.
• Deliver quickly with visible incremental progress.
• Avoid over-engineering and adapt to feedback and changing priorities.
• Communicate clearly with stakeholders while remaining engaged and accountable.
• Work independently and take ownership of deliverables.

• Bachelor’s or Master’s degree in Computer Science, Engineering or a related field.
• Consulting or IT-services experience with direct, daily client communication.
• Relevant certifications such as Cognigy, AWS AI/GenAI, IREB CPRE or ISTQB.
• Strong English communication skills at C1 level or higher.

Must-Have Skills (2+ Years)

• Hands-on experience with at least one Conversational AI platform: Cognigy.AI, Amazon Bedrock AgentCore, Amazon Connect, Amazon Lex, Google CCAI, Kore.ai, Microsoft Bot Framework, Parloa
• Strong JavaScript/TypeScript and Node.js skills for scripting, extensions and API integrations.
• Practical experience consuming REST APIs and integrating third-party systems.
• Experience with RESTful APIs, GraphQL or gRPC.
• Experience with Git, Jira and Confluence.

Should-Have Skills (1+ Year)

• Java or Python for data transformation, scripting or backend integration.
• AI-agent orchestration, including hybrid deterministic and GenAI flows.
• LLM concepts including context windows, tokens, embeddings, temperature and RAG.
• System prompts, personas, guardrails, MCP or similar tool-use/function-calling patterns.
• Experience with AWS, Azure or GCP; AWS preferred.
• CI/CD using GitLab CI, Azure DevOps or similar tools.

Nice-to-Have Skills (0.5+ Year)

• AI/Agentic Coding tools such as Anthropic Claude, OpenAI Codex or GitHub Copilot.
• GDPR, EU AI Act and enterprise AI knowledge.
• RAG using Pinecone, Weaviate or pgvector.
• SSO technologies such as OAuth2, OpenID Connect, JWT or SAML.
• Cloud contact centre or voice AI experience with Amazon Connect or Genesys Cloud CX.
• CCaaS and telephony technologies such as PBX, SBC, TTS or ASR.
• Event streaming using Kafka, AWS SQS or AWS SNS.
• Kubernetes and container platforms such as EKS/ECS, AKS or GKE.
• Infrastructure as Code using Terraform.
• Observability tools such as Datadog, Dynatrace or CloudWatch.