Associate Lead - Testing (QA + MLOps)
Quantiphi is seeking a Lead QA Engineer to define and execute quality strategies for AI/ML and Generative AI systems within the AWS ecosystem. The role involves designing validation frameworks for LLMs, MLOps pipelines, and agentic workflows while leading client-facing strategy workshops. You will build reusable automation harnesses using Python and AWS-native tools to ensure model performance, safety, and reliability. This is a senior, high-impact role requiring deep expertise in AI quality engineering and leadership.
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Experience
10+ years
Function
Quality Assurance
Work mode
Hybrid, India
Company
Tier 2
What you will work on
Quantiphi is seeking a Lead QA Engineer to define and execute quality strategies for AI/ML and Generative AI systems within the AWS ecosystem. The role involves designing validation frameworks for LLMs, MLOps pipelines, and agentic workflows while leading client-facing strategy workshops. You will build reusable automation harnesses using Python and AWS-native tools to ensure model performance, safety, and reliability. This is a senior, high-impact role requiring deep expertise in AI quality engineering and leadership.
TAL's take
Strong role scope with heavy emphasis on specialized AI/ML quality strategy and leadership in a reputable niche firm.
Extremely well-defined responsibilities, technical stack, and domain focus on AWS-based AI/ML/GenAI quality engineering.
Salaries at Quantiphi
14.3 LPA average
Based on 54 Grapevine salary entries for Quantiphi.
Operations
0 - 2 years | L1
4 LPA average
Range: 4 - 4 LPA
Sales
0 - 2 years | L1
7 LPA average
Range: 6 - 7 LPA
Engineering
0 - 2 years | L1
6 LPA average
Range: 6 - 6 LPA
Other roles
0 - 2 years | L1
8 LPA average
Range: 6 - 10 LPA
Must haves
- 10+ years in quality engineering
- Strong test strategy, automation, and governance experience
- Hands-on experience with Amazon SageMaker and Bedrock
- Expertise in Python for test framework development
- Experience validating LLM and RAG applications
- Proven experience leading QA transformation initiatives
Tools and skills
Nice to have: terraform, cloudformation.
About the company
Established mid-stage AI-focused services company with a significant global presence.
Posts mentioning Quantiphi
Need help and advice please😭🙏🏻
Hi All, I have recently switched from Accenture to Quantiphi. 6th April was the last working day at Accenture and 13th April was my onboarding with Quantiphi. I have around 5 years of working experience as a data engineer, working with SQL, GCP tools, BigQuery, Cloud Composer, Airflow, SSIS, SSRS. During the interview and the job description that Quantiphi gave was perfectly aligning with my skills. But today was the day I am feeling completely lost and broken with no idea on what to do next. I got the project details today and my task here would be, for a client, for a new geographic location they want to expand their business where Azure or GCP or Azure has limited rules, so Alibaba cloud is what they want to use. Now my task would involve about, whatever services they were using in Azure, those same replicas or other concepts how we can achieve or available in Alibaba, those POCs I need to work with. I was completely blank after hearing this. This is so new to me, although learning is not something that I am running away from, but this is not aligned with my skill set and this is not something a data engineer does. My task was to make raw data consumable and help the leadership team in making data driven decisions. Please do genuinely advise me on the next steps what should I do, whom should I reach out to. I am having a breakdown today and been questioning the choice I made choosing this over General Mills as it was paying less. Atleast a product based company won’t do this. I want someone to talk to. Please please help me out guys😭😭
How is Quantiphi analytics work culture and WLB?
Is it good to join Quantiphi as data engineer from a renowned product based company? How is work culture? Learning and pay?
Rate My Techstack: Potential Data Engineering Roles
I will be using a scale of 10 for better quantification. Python : 7/10 SQL: 7/10 PowerBI: 9/10 ML(Pandas): 6/10 PLSQL: 6/10 Advanced Excel: 8/10 Azure Databricks + DataFactory : Started learning Apache Spark: Started learning Communication skills: 9/10 Prior Work Ex: 1.8yrs as a PLSQL developer (started off as a fresher) + one SAP internship of 4months + one Data analyst internship of 1 month Aspiration : Data Engineering Role 1. Is the above techstack enough to get me a good data engineering role? Will I be able to clear the technical rounds at companies like accenture, IBM etc with this profile? I have heard the barrier to entry for data engineering is higher than that of data analyst. 2. Do I need to learn DSA? 3. What salary range do I fall in with this profile? I seek your honest answer. I feel lost. Also, should I focus more on improving my cloud skills or shall I be more competent with my python skills? Which one would pay me off in a better sense financially? I certainly can not focus on all the tools at once.