Manager - Customer Interaction Suite - Customer Interaction Suite

About The Company
Tata Communications Redefines Connectivity with Innovation and IntelligenceDriving the next level of intelligence powered by Cloud, Mobility, Internet of Things, Collaboration, Security, Media services and Network services, we at Tata Communications are envisaging a New World of Communications
Broad outline of the Role
As an AI Software Developer, you will design, develop, and own end to end AI solutions for Dark NOC, an AI driven automation platform for customer operations support. You will be responsible for full stack AI development, covering model integration, application logic, APIs, workflows, and production readiness. In this role, you will work closely with the Project Manager to translate business and operational requirements into scalable, reliable, and automated AI capabilities. You will build and productionize solutions leveraging LLMs, NLP, RAG based systems, and automation workflows to enable proactive issue detection, intelligent troubleshooting, and autonomous operations. You will take complete ownership of the development lifecycle from design and implementation to testing, deployment, and optimization ensuring the Dark NOC platform delivers secure, cost efficient, measurable, and SLA aligned AI automation for enterprise customer operations. Graduate in Engineering Experience 4 10 years
Minimum Qualifications & Experience
Bachelor s degree in engineering 4-10 Years relevant experience
Core Knowledge & Skills
Proficiency in Python programming, Node.js, V S Code,
Strong hands-on experience with LLMs (Llama, Mistral, Claude, etc.)
RAG (Retrieval Augmented Generation) design & implementation
Prompt engineering (design, tuning, evaluation)
Embeddings & vector databases (FAISS, Pinecone, etc.)
Function/tool calling APIs for automation
Experience with LangChain / LlamaIndex
Experience integrating AI models using LLM function/tool calling APIs for automated decision making and actions.
Strong programming skills in Python node.js or building scalable APIs and services
Proficiency in Git for source control and collaborative development.
Strong hands on experience with REST and gRPC APIs, including HTTP status codes, Payload structures, Rate limiting, retries, and error handling.
ML Tooling: scikit learn, transformers; experiment tracking (eg MLflow/Weights & Biases); model registry.
MLOps/DevOps: Git, CI/CD (GitHub/GitLab/Azure DevOps), Docker, Kubernetes; API gateways.
Observability: Prometheus, Grafana, ELK/EFK, Loki; log/metrics correlation; cost/latency dashboards.
Security & Compliance: Secrets management (Vault/Key Vault/SM), token hygiene, PII redaction, RBAC, audit logging.
Hands on experience using Visual Studio Code (preferred for Python) and Visual Studio (with Python workload), along with Git and Docker for local development and containerized builds, with active usage in both C#/.NET and Python development, including debugging, code reviews, and collaborative development workflows.
Minimum 4-10 years of hands on development experience with MySQL or PostgreSQL.
Other Knowledge & Skills
Ability to understand business goals and map to technical requirements.
Exposure towards working in the RFP cases.
Knowledge of creating HLD and LLD
Good understanding of use cases and able to create solutions relating to the use cases.
Proficient with MS Office tools Word, Excel, Access, Power point, Visio
Understanding of technology and services related to the domain.
Key Responsibilities
End to End Solution Design & Development
Translate business and operational requirements into architecture, user stories, and technical designs for Dark NOC features.
Build full stack AI capabilities: model integration (LLMs/NLP), orchestration logic, APIs/services, and workflow automation.
Implement RAG pipelines (data ingestion, chunking, embeddings, vector search) and tool/function calling for autonomous actions.
Model Integration & Prompt Engineering
Integrate LLMs/NLU/ASR/TTS providers with robust adapters, retries, timeouts, and fallbacks.
Design and maintain prompts, system policies, and tool schemas; evaluate and refine prompts for accuracy and reliability.
Implement guardrails (policy enforcement, PII masking, safety filters) and quality evaluation (e.g., RAG ground truth checks).
Data Engineering for Dark NOC
Build data ingestion & transformation for logs, alerts, tickets, and knowledge bases.
Maintain feature/knowledge freshness SLAs and data contracts with upstream systems.
Integration with New Relic, Service Now, Email, chat, REST API for end-to-end automation.
Testing, Quality & Evaluations
Implement unit/integration/e2e tests, plus AI evaluations (groundedness, hallucination, toxicity).
Create offline and shadow/A B evaluations for prompts, models, and RAG changes before production rollout.
Define acceptance criteria with the Project Manager; maintain a robust regression suite.
CI/CD & Operations Ready Builds
Set up CI/CD pipelines with canary/blue green releases, automated rollbacks, and migration/versioning for prompts, models, and indexes.
Containerize services (Docker) and deploy to Kubernetes with observability hooks and resource limits.
Produce runbooks and operational toggles (feature flags, kill switches, fallback modes).
Collaboration & Delivery Management
Work closely with the Project Manager on scope, estimations, milestones, and risk tracking.
Partner with platform, infra, and data teams to unblock dependencies and align environments and SLAs.
Provide clear documentation (designs, APIs, runbooks, evaluation results) and demo increments to stakeholders.
Production Support (L3 Level)
Support pre prod validations and production rollouts; analyze incidents with traces/logs and drive code fixes.
Own RCA for code/config issues and convert findings into tests, guardrails, and automation.
KPIs
Feature Delivery Predictability: % of committed Dark NOC stories delivered per sprint / quarter.
Deployment Frequency: Target: 2-4 per week
Change Failure Rate:Target: 8-10%
Defect Escape Rate:Target: 10-15%
AI Effectiveness: Target: 90%
Auto Remediation Success: Target: 60% for repeatable issues
Preferred Trainings/Certifications
Certification - Generative AI with Large Language Models or LLMOps
Certified in C# (.NET) or Python
Certification or deep knowledge of SDLC, Agile, or DevOps methodologies

Work arrangement
No