Technical Architect

Prodapt Solutions Private Limited; Chennai District; On-site; INR 400,000 - 700,000; Full time

Job summary

Prodapt Solutions Private Limited seeks a Technical Architect to lead the engineering direction of our AI-native platform. You will own end-to-end technical architecture across core systems, AI/ML platform, data infra, APIs, and integration layers, translating product requirements into scalable designs.

You will define technology choices, enforce security and CI/CD practices, and mentor a team of Forward Deployment Engineers.

Qualifications

• Strong product engineering experience on the listed platforms (ServiceNow, Salesforce, Netcracker, Amdocs, Ericson).
• Expert-level software engineering in Python/Go/Java with cross-stack skills.
• Deep experience in distributed systems, microservices, and event-driven architectures.
• Hands-on AI/ML platform engineering: LLM integration, vector databases, RAG pipelines.

Responsibilities

• Own end-to-end technical architecture across core, AI/ML platform, data infra, APIs and integration layers.
• Translate PRDs into detailed technical designs and engineering specs.
• Make authoritative technology choices: frameworks, cloud, data stores, LLM tooling.
• Define and enforce engineering standards: security, CI/CD, performance SLOs.
• Lead and mentor Forward Deployment Engineers; conduct architecture/code reviews.
• Identify and mitigate technical risks; build observability into product layers.
• Collaborate with Product Architect on feasibility, trade-offs and buy/build decisions.
• Drive prototype-to-production excellence; own debt strategy and platform roadmap.

Skills

ServiceNow

Salesforce

Netcracker

Amdocs

Ericson

Polyglot programming

Distributed systems

LLM integration

Kubernetes

Cloud platforms

Education

B.S./M.S. in CS/Engineering

Tools

Python

Go

Java

Terraform

Job description

Overview

ROLE : The Technical Architect is the engineering owner of the product. They receive business requirements from the Product Architect and translate them into coherent technical strategies - choosing the right technology stack, defining system design, and leading the engineering team to build products that are scalable, secure, and future-ready. Within Prodapt's AI-native portfolio, this role is the custodian of platform integrity and the technical compass for all engineering decisions.

Responsibilities

CORE RESPONSIBILITIES

• Own end-to-end technical architecture across core, AI/ML platform, data infrastructure, APIs, and integration layers.
• Translate product requirements (PRDs) into detailed technical designs, system diagrams, & engineering specifications.
• Make authoritative technology choices: frameworks, cloud providers, data stores, AI/LLM orchestration tooling with clear rationale.
• Define and enforce engineering standards: coding guidelines, security posture, performance SLOs, and CI/CD practices.
• Lead, mentor, and grow a team of Forward Deployment Engineers - conduct architecture and code reviews.
• Identify and mitigate technical risks early; build resilience and observability into every product layer.
• Collaborate with Product Architect on feasibility, trade-off analysis, and build-vs-buy decisions.
• Drive prototype-to-production engineering excellence; own technical debt strategy and platform evolution roadmap.

MUST-HAVE SKILLS & EXPERIENCE

• Strong product engineering experience in one of the platforms: ServiceNow, Salesforce, Netcracker, Amdocs, Ericson.
• Expert-level software engineering in Python, Go, or Java with strong polyglot instincts across the stack.
• Deep experience designing distributed systems, microservices, and event-driven architectures at scale.
• Hands-on AI/ML platform engineering: LLM integration, vector databases, RAG pipelines, model serving (vLLM,Ollama, TensorRT-LLM, Triton, etc.).
• Cloud-native expertise across AWS / Azure / GCP: Kubernetes, Terraform, observability stacks, and FinOps.
• Strong data engineering background: streaming (Kafka/Flink), warehousing (Snowflake/BigQuery), and lineage tooling.
• Security-first mindset: zero-trust networking, secrets management, vulnerability remediation at the infra layer.

MINDSET & BEHAVIOURS

• Pragmatic visionary - balances architectural elegance with delivery speed and operational reality.
• Trusted technical authority - engineers follow their lead; can say no with reasoned alternatives.
• Systems thinker - sees second-order effects of technology choices on cost, scalability, and team velocity.
• Continuous learner - actively evaluates emerging AI/ML tooling and brings proven innovations to the team.

Requirements

MUST-HAVE SKILLS & EXPERIENCE

• Strong product engineering experience in one of the platforms: ServiceNow, Salesforce, Netcracker, Amdocs, Ericson.
• Expert-level software engineering in Python, Go, or Java with strong polyglot instincts across the stack.
• Deep experience designing distributed systems, microservices, and event-driven architectures at scale.
• Hands-on AI/ML platform engineering: LLM integration, vector databases, RAG pipelines, model serving (vLLM,Ollama, TensorRT-LLM, Triton, etc.).
• Cloud-native expertise across AWS / Azure / GCP: Kubernetes, Terraform, observability stacks, and FinOps.
• Strong data engineering background: streaming (Kafka/Flink), warehousing (Snowflake/BigQuery), and lineage tooling.
• Security-first mindset: zero-trust networking, secrets management, vulnerability remediation at the infra layer.

MINDSET & BEHAVIOURS

• Pragmatic visionary - balances architectural elegance with delivery speed and operational reality.
• Trusted technical authority - engineers follow their lead; can say no with reasoned alternatives.
• Systems thinker - sees second-order effects of technology choices on cost, scalability, and team velocity.
• Continuous learner - actively evaluates emerging AI/ML tooling and brings proven innovations to the team.

PREFERRED QUALIFICATIONS

• B.S. / M.S. in Computer Science, Systems Engineering, or related field.
• Published architecture patterns, open-source contributions, or conference talks in AI/infra domain.
• Experience as a technical lead in a telecom, network automation, or enterprise SaaS environment.