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Designation: Kafka Consultant

Job Description:

• 3-8+ years of experience programming in a backend language (Java / Python), with a good understanding of troubleshooting errors.
• 5+ years of experience in Confluent Kafka / 3+ years of experience in Confluent Kafka
• Cloud Kafka, Control Central, Rest Proxy, HA Proxy, Confluent Kafka Connect, Confluent Kafka Security features
• 3-5+ years of working experience with different databases such as Oracle/Mysql/MongoDB/Snowflake/RDS databases.
• 3-5+ years of experience with AWS/GCP/Azure preferred AWS. AWS Solutions Architect certifications are preferred.
• 2+ years of experience with Monitoring tools (Prometheus, Grafana / Spl
• Proficient in building/scaling large systems end to end using Tibco BW5, BW6 or other high-performance languages,
• developer tools, CI/CD, DevOps, GitHub, Terraform, and Ansible.

Required Skills for the Java role :

• Experience in Core Java, CXF, Spring.
• Experience in spring boot, microservices.
• Extensive experience in developing enterprise-scale n-tier applications for the financial domain. Should possess good architectural knowledge and be aware of enterprise application design patterns.
• Should have the ability to analyze, design, develop and test complex, low-latency client-facing applications.
• Good development experience with RDBMS, preferably Sybase database
• Good knowledge of multi-threading and high volume server side development
• Experience in sales and trading platforms in investment banking/capital markets
• Basic working knowledge of Unix/Linux
• Excellent problem solving and coding skills in Java
• Strong interpersonal, communication and analytical skills.
• Should have the ability to express their design ideas and thoughts.
• Bachelor's/Master’s degree in Computer Science or related field from a top-tier institute (IIT, NIT, BITS, etc.).

Job Title: AI/ML Engineer – Voice (2–3 Years)

Location: Bengaluru (On-site)

Employment Type: Full-time

About Impacto Digifin Technologies

Impacto Digifin Technologies enables enterprises to adopt digital transformation through intelligent, AI-powered solutions. Our platforms reduce manual work, improve accuracy, automate complex workflows, and ensure compliance—empowering organizations to operate with speed, clarity, and confidence.

We combine automation where it’s fastest with human oversight where it matters most. This hybrid approach ensures trust, reliability, and measurable efficiency across fintech and enterprise operations.

Role Overview

We are looking for an AI Engineer Voice with strong applied experience in machine learning, deep learning, NLP, GenAI, and full-stack voice AI systems.

This role requires someone who can design, build, deploy, and optimize end-to-end voice AI pipelines, including speech-to-text, text-to-speech, real-time streaming voice interactions, voice-enabled AI applications, and voice-to-LLM integrations.

You will work across core ML/DL systems, voice models, predictive analytics, banking-domain AI applications, and emerging AGI-aligned frameworks. The ideal candidate is an applied engineer with strong fundamentals, the ability to prototype quickly, and the maturity to contribute to R&D when needed.

This role is collaborative, cross-functional, and hands-on.

Key Responsibilities

Voice AI Engineering

• Build end-to-end voice AI systems, including STT, TTS, VAD, audio processing, and conversational voice pipelines.
• Implement real-time voice pipelines involving streaming interactions with LLMs and AI agents.
• Design and integrate voice calling workflows, bi-directional audio streaming, and voice-based user interactions.
• Develop voice-enabled applications, voice chat systems, and voice-to-AI integrations for enterprise workflows.
• Build and optimize audio preprocessing layers (noise reduction, segmentation, normalization)
• Implement voice understanding modules, speech intent extraction, and context tracking.

Machine Learning & Deep Learning

• Build, deploy, and optimize ML and DL models for prediction, classification, and automation use cases.
• Train and fine-tune neural networks for text, speech, and multimodal tasks.
• Build traditional ML systems where needed (statistical, rule-based, hybrid systems).
• Perform feature engineering, model evaluation, retraining, and continuous learning cycles.

NLP, LLMs & GenAI

• Implement NLP pipelines including tokenization, NER, intent, embeddings, and semantic classification.
• Work with LLM architectures for text + voice workflows
• Build GenAI-based workflows and integrate models into production systems.
• Implement RAG pipelines and agent-based systems for complex automation.

Fintech & Banking AI

• Work on AI-driven features related to banking, financial risk, compliance automation, fraud patterns, and customer intelligence.
• Understand fintech data structures and constraints while designing AI models.

Engineering, Deployment & Collaboration

• Deploy models on cloud or on-prem (AWS / Azure / GCP / internal infra).
• Build robust APIs and services for voice and ML-based functionalities.
• Collaborate with data engineers, backend developers, and business teams to deliver end-to-end AI solutions.
• Document systems and contribute to internal knowledge bases and R&D.

Security & Compliance

• Follow fundamental best practices for AI security, access control, and safe data handling.
• Awareness of financial compliance standards (plus, not mandatory).
• Follow internal guidelines on PII, audio data, and model privacy.

Primary Skills (Must-Have)

Core AI

• Machine Learning fundamentals
• Deep Learning architectures
• NLP pipelines and transformers
• LLM usage and integration
• GenAI development
• Voice AI (STT, TTS, VAD, real-time pipelines)
• Audio processing fundamentals
• Model building, tuning, and retraining
• RAG systems
• AI Agents (orchestration, multi-step reasoning)

Voice Engineering

• End-to-end voice application development
• Voice calling & telephony integration (framework-agnostic)
• Realtime STT ↔ LLM ↔ TTS interactive flows
• Voice chat system development
• Voice-to-AI model integration for automation

Fintech/Banking Awareness

• High-level understanding of fintech and banking AI use cases
• Data patterns in core banking analytics (advantageous)

Programming & Engineering

• Python (strong competency)
• Cloud deployment understanding (AWS/Azure/GCP)
• API development
• Data processing & pipeline creation

Secondary Skills (Good to Have)

• MLOps & CI/CD for ML systems
• Vector databases
• Prompt engineering
• Model monitoring & evaluation frameworks
• Microservices experience
• Basic UI integration understanding for voice/chat
• Research reading & benchmarking ability

Qualifications

• 2–3 years of practical experience in AI/ML/DL engineering.
• Bachelor’s/Master’s degree in CS, AI, Data Science, or related fields.
• Proven hands-on experience building ML/DL/voice pipelines.
• Experience in fintech or data-intensive domains preferred.

Soft Skills

• Clear communication and requirement understanding
• Curiosity and research mindset
• Self-driven problem solving
• Ability to collaborate cross-functionally
• Strong ownership and delivery discipline
• Ability to explain complex AI concepts simply

• We are looking for a Senior SRE with a proven track record of success leading complex cloud-hybrid environments. You will have:
• Strong sense of Being an Owner, Wearing the Customer Shoes, with the ability to Empower Others demonstrated through clear
• communication and collaboration.
• Skills to work independently with multiple global teams, developing, configuring, deploying, and operating our global infrastructure on AWS and on-prem.
• Operational experience in complex distributed and real-time systems, including experience with SLO/SLAs towards high availability,reliability and DR goals.
• DevOps experience in building tools and frameworks, with an understanding of continuous deployment processes.
• Ability to think at scale, bringing a focus on continuous delivery methodologies from design through deployment and operations.
• Experience building and managing systems with tools including Kubernetes, Chef/Ansible/Puppet, Kafka, Docker, and Terraform.

• 5+ years experience in a Software and/or Site Reliability Engineering role
• Experience writing automation code in GoLang, Python or Java
• Experience developing and operating large scale distributed systems with Kubernetes and Docker
• Experience in running real time and low latency high available applications (Kafka, gRPC, RTP)
• Experience running public cloud environments on AWS
• Experience running hybrid clouds and on-prem infrastructures on Red Hat Enterprise Linux / CentOS
• Bachelor degree in Engineering, Computer Science or equivalent experience
• The ability to lead, partner, and collaborate cross functionally across an engineering organization

Please find below the required skill set

Skillsets:

• Strong Experience in Ruby on Rails
• Solid understanding of Ruby principles and core concepts.
• Good understanding of Object Oriented Concepts and principles.
• Understanding of RESTful/ SOAP APIs.
• Good understanding of front-end technologies including HTML5, CSS3, JavaScript, jQuery, ReactJS and Bootstrap framework.
• Knowledge/ Experience in SQL and PL/SQL programming.
• Excellent communication Skill.