Accolite

Director – Technical Solutions & Engineering / Solutions Architect

Posted On

Oct. 29, 2025

Location

Bangalore, Karnataka

Experience Level

15 - 25 Years Exp.

Job Type

Contract

Apply By

Dec. 6, 2025

Job Description

Role Overview

The Technical Solutions & Engineering Director is a hands-on technology leader responsible for architecting and delivering enterprise-grade, cloud-native, and AI-enabled solutions. The role demands strong technical depth in Java, Microservices, React, and Kafka, combined with the ability to conceptualize and integrate AI-driven capabilities into modern digital platforms.
This leader will bridge business goals and technology implementation — driving innovation, pre-sales support, and delivery excellence.

Key Responsibilities

1. Solution Architecture & Design

Architect scalable, secure, and high-performance enterprise applications using Java (Spring Boot) and Microservices architecture.
Design event-driven and streaming architectures leveraging Apache Kafka for real-time processing and data pipelines.
Lead frontend architecture using React and modern UI frameworks for responsive, high-performing web applications.
Integrate AI and machine learning components into enterprise solutions — such as personalization, predictive analytics, chatbots, and process automation.
Define architecture patterns, technical roadmaps, and modernization strategies aligned with client business goals.

2. Pre-Sales & Solutioning

Collaborate with business and sales teams to craft winning proposals, RFP responses, and solution blueprints.
Conceptualize and demonstrate AI-powered solutions using ML models, NLP, and cloud AI services (AWS SageMaker, Azure AI, Vertex AI, OpenAI APIs, etc.).
Lead technical discovery, estimation, and architecture definition workshops with clients.
Prepare and deliver high-impact technical presentations, whitepapers, and PoCs.

3. Implementation & Delivery Leadership

Provide hands-on technical leadership during the entire delivery lifecycle.
Guide engineering teams on best practices in Java, Microservices, React, and Kafka ecosystems.
Ensure architectural consistency, scalability, and quality during implementation.
Drive DevOps maturity — containerization (Docker, Kubernetes), CI/CD automation, and observability setup.
Oversee AI solution implementation — integrating APIs, data pipelines, and MLOps workflows.

4. Innovation & Technology Leadership

Identify opportunities to embed AI/ML, data analytics, and automation in client solutions.
Lead the creation of accelerators, reusable components, and frameworks across Cloud, Microservices, and AI ecosystems.
Stay abreast of emerging tech (Generative AI, LLMs, edge computing, serverless architecture) and assess their business value.
Drive internal R&D and proof-of-concepts showcasing innovative technical capabilities.

5. People & Stakeholder Leadership

Build and mentor a strong architecture and engineering team.
Partner with delivery, data, and AI teams for end-to-end solution ownership.
Establish architecture governance, knowledge sharing, and technical excellence practices.
Act as a trusted advisor to CXOs and client technology leaders.

Key Technical Skills

Core Technologies

Backend: Java 11+, Spring Boot, Spring Cloud, Hibernate, JPA.
Architecture: Microservices, Event-Driven Architecture, Domain-Driven Design (DDD), REST & GraphQL APIs.
Frontend: React, Redux, TypeScript, HTML5, CSS3.
Messaging & Streaming: Apache Kafka, RabbitMQ, ActiveMQ.
Databases: PostgreSQL, MongoDB, Redis, Cassandra.
DevOps: Docker, Kubernetes, Jenkins, GitHub Actions, Terraform, Helm.
Cloud Platforms: AWS / Azure / GCP (hands-on experience with architecture and deployment).

AI & Data Skills

Understanding of AI/ML fundamentals — model training, deployment, and inference.
Experience integrating AI services (OpenAI, AWS SageMaker, Azure Cognitive Services, Google Vertex AI).
Familiarity with NLP, computer vision, and data engineering concepts.
Exposure to MLOps pipelines and API-based AI solution integration.
Ability to identify business use cases for AI/ML within client environments.

Qualifications

Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.
15+ years of experience in software engineering, architecture, and delivery.
At least 5 years in a senior technical or solution architecture leadership role.
Proven expertise in Java, Microservices, React, Kafka, and exposure to AI/ML-driven applications.
Certifications preferred: AWS / Azure Architect, TOGAF, or AI-related specialization.

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